Method and system for realizing maritime medical real-time response and scheduling based on adaptive satellite and ground network switching

Abstract

The invention provides a method and a system for realizing maritime medical real-time response and scheduling based on adaptive satellite and ground network switching. The method comprises the following steps: receiving an emergency medical help signal from a marine ship or platform, and generating an emergency medical event comprehensive report; according to the emergency medical event comprehensive report, sea area dynamic meteorological data and ocean current prediction are combined, an intelligent resource matching algorithm is applied, and an optimal medical response unit is obtained; based on the optimal medical response unit, a disease progress prediction algorithm is adopted, a historical case library and real-time physiological parameter monitoring data are analyzed and processed, accurate treatment suggestions and guidance are provided, and a remote medical support and treatment scheme is obtained; and generating a detailed scheduling action plan based on the telemedicine support and treatment scheme. According to the technical scheme provided by the invention, the speed and accuracy of emergency response of offshore medical treatment are remarkably improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of satellite communication technology, and in particular to a method and system for implementing real-time response and scheduling of medical treatment at sea based on adaptive satellite and ground network switching. Background Art

[0002] In the vast ocean environment, personnel on offshore vessels or platforms may encounter emergency medical situations, such as sudden illness or accidental injury. In these situations, timely and effective medical assistance is essential. However, due to the complexity of the marine environment and the particularity of remote locations, traditional ground medical services are difficult to respond quickly. Therefore, there is an urgent need for an efficient and reliable emergency response system that can receive emergency medical help signals from offshore vessels or platforms through adaptively selected satellite communication networks or ground 5G networks, process and obtain the precise geographic coordinates of the help location, environmental conditions and preliminary diagnosis information of patients, and generate a comprehensive report on emergency medical events. The system must also have the ability to dynamically evaluate and deploy medical resources to ensure the rapid deployment and effective implementation of rescue operations.

[0003] At present, medical emergency response at sea mainly relies on traditional radio communications and limited satellite phone services. When an emergency medical incident occurs, the crew usually calls for help from the shore via radio or satellite phone, providing verbal descriptions of help information. Subsequently, the land medical center conducts a preliminary assessment based on the limited information and dispatches the nearest medical rescue resources to rescue. In addition, some advanced ships are equipped with basic medical equipment and remote medical consultation systems, but the functions of these systems are relatively simple and cannot provide comprehensive condition analysis and real-time guidance.

[0004] Existing solutions have several significant flaws: the information provided by traditional communication methods is often not detailed and accurate enough, making it difficult for medical centers to fully understand the specific conditions at the scene of the help-seeking, affecting the quality of rescue decisions; due to the lack of intelligent resource matching algorithms and dynamic path planning tools, the scheduling efficiency of medical resources is low, delaying the best time for treatment; the existing telemedicine consultation system has limited functions and cannot provide high-definition video connections and real-time physiological parameter monitoring, which limits experts' precise guidance of patients and reduces treatment effectiveness. Summary of the invention

[0005] The embodiments of the present application provide a method and system for implementing real-time medical response and scheduling at sea based on adaptive satellite and ground network switching, so as to solve the problems of slow speed and poor accuracy of emergency medical response at sea in the prior art.

[0006] In a first aspect, an embodiment of the present application provides a method for implementing real-time response and scheduling of medical services at sea based on adaptive satellite and terrestrial network switching, including:

[0007] Through adaptively selected satellite communication networks or ground 5G networks, emergency medical assistance signals from offshore vessels or platforms are processed and obtained, including precise geographic coordinates of the assistance location, environmental conditions, and preliminary patient diagnosis information, to generate a comprehensive report on emergency medical events;

[0008] Based on the comprehensive report of the emergency medical incident, combined with the dynamic meteorological data of the sea area and the ocean current forecast, the intelligent resource matching algorithm is applied to evaluate the time and feasibility of different marine medical rescue resources arriving at the place of help, and the influence of weather changes and sea conditions is analyzed through the sensitivity analysis technology of influencing factors to ensure that the selected medical response unit operates efficiently under various conditions and obtain the most suitable medical response unit;

[0009] Based on the most suitable medical response unit, a high-definition video connection is established between the scene of the call for help and the land medical center using a two-way satellite link, and a remote medical decision-making support system is introduced. The disease progression prediction algorithm is used to analyze and process the historical case database and real-time physiological parameter monitoring data to provide accurate treatment suggestions and guidance, and obtain remote medical support and treatment plans;

[0010] Based on the telemedicine support and treatment plan, the optimal transfer route to the nearest port or island with medical facilities is dynamically planned, taking into account the legal constraints of international waters, the possibility of medical support along the way and the urgency of the patient's condition, and generating a detailed scheduling action plan.

[0011] Optionally, the comprehensive report on the emergency medical incident, combined with dynamic meteorological data of the sea area and ocean current forecasts, applies an intelligent resource matching algorithm to evaluate the time and feasibility of different marine medical rescue resources arriving at the place of help, analyzes the impact of weather changes and sea conditions through influencing factor sensitivity analysis technology, ensures that the selected medical response unit operates efficiently under various conditions, and obtains the most suitable medical response unit, including:

[0012] Using the comprehensive emergency medical incident report, conduct a preliminary assessment of the location information of different maritime medical rescue resources and their accessibility and transportation safety to obtain a preliminary response effectiveness evaluation;

[0013] Based on the preliminary response effectiveness evaluation, combined with the dynamic meteorological data of the sea area and the ocean current forecast, the intelligent resource matching algorithm is applied to quantitatively evaluate the time and feasibility of each medical rescue resource arriving at the place of help, and generate a medical rescue resource evaluation result;

[0014] Based on the medical rescue resource assessment results, the influencing factor sensitivity analysis technology is used to deeply analyze the weather changes and sea conditions to obtain an influencing factor analysis report;

[0015] The influencing factor analysis report is used to conduct a final review of the operating efficiency of each medical rescue resource under different conditions to ensure that the selected medical response unit can operate efficiently under various conditions and obtain the most suitable medical response unit.

[0016] Optionally, based on the medical rescue resource assessment result, the influencing factor sensitivity analysis technology is used to perform in-depth analysis and processing on weather changes and sea conditions to obtain an influencing factor analysis report, including:

[0017] Using the medical rescue resource assessment results, data on weather changes and sea conditions are collected and processed to generate an original influencing factor data set;

[0018] Based on the original influencing factor data set, a multi-factor comprehensive evaluation model is applied to quantitatively analyze the importance and mutual relationship of each factor to generate a factor importance score table;

[0019] Based on the factor importance score table, combined with the successful experiences and lessons learned from historical rescue cases, the potential impact of each influencing factor is deeply analyzed and processed to obtain the influencing factor analysis results;

[0020] The analysis results of the influencing factors are integrated to form a comprehensive influencing factor analysis report.

[0021] Optionally, the influencing factor analysis report is used to conduct a final review of the operating efficiency of each medical rescue resource under different conditions to ensure that the selected medical response unit can operate efficiently under various conditions and obtain the most suitable medical response unit, including:

[0022] Using the influencing factor analysis report, the operational efficiency of each medical rescue resource under different weather conditions and sea conditions is quantitatively evaluated to obtain an operational efficiency score;

[0023] Based on the operational efficiency score and combined with the successful experiences and lessons learned in the historical rescue case library, a comprehensive evaluation is conducted on the adaptability and reliability of each medical rescue resource to generate a medical rescue resource adaptability report;

[0024] Based on the medical rescue resource adaptability report, a multi-dimensional performance optimization algorithm is applied to conduct a final review of the overall performance of each medical rescue resource to determine the optimal medical response unit;

[0025] The optimal medical response unit is confirmed to ensure that it can operate efficiently under various conditions, and ultimately the most suitable medical response unit is generated.

[0026] Optionally, the most suitable medical response unit uses a two-way satellite link to establish a high-definition video connection between the help-seeking site and the land medical center, and introduces a remote medical decision-making support system, adopts a disease progression prediction algorithm, analyzes and processes the historical case database and real-time physiological parameter monitoring data, provides accurate treatment suggestions and guidance, and obtains remote medical support and treatment plans, including:

[0027] Utilizing the optimal medical response unit, combined with high-precision positioning technology and two-way satellite link technology, to configure and optimize the high-definition video connection between the scene of the call and the land-based medical center, ensuring stable, low-latency communication quality, and obtaining high-definition video connection support;

[0028] Based on the HD video connection support, a remote medical decision-making support system is introduced, integrating two-way video consultation and disease tracking functions, realizing real-time interaction and guidance between the help-seeking site and land medical experts, and generating a comprehensive remote medical monitoring platform;

[0029] Based on the remote medical monitoring platform, the disease progression prediction algorithm is applied to comprehensively analyze and process similar cases in the historical case database and the real-time physiological parameter monitoring data at the scene of help-seeking, and provide accurate treatment suggestions and guidance in combination with the patient's personalized factors, and generate a personalized preliminary treatment plan;

[0030] The personalized preliminary treatment plan is used in combination with the real-time feedback provided by the telemedicine monitoring platform and the professional opinions of the expert system, and comprehensive evaluation and adjustment are performed through an intelligent optimization algorithm to obtain telemedicine support and treatment plans.

[0031] Optionally, the personalized preliminary treatment plan is used in combination with the real-time feedback provided by the telemedicine monitoring platform and the professional opinions of the expert system, and a comprehensive evaluation and adjustment is performed through an intelligent optimization algorithm to obtain telemedicine support and treatment plans, including:

[0032] Using the personalized preliminary treatment plan, the patient's current condition and possible development trend are estimated and processed, and a condition estimation report is generated;

[0033] According to the disease prediction report, combined with the high-definition video connection support and real-time physiological parameter monitoring data provided by the remote medical monitoring platform, the actual situation of the patient is continuously tracked and dynamically evaluated to obtain a real-time disease tracking record;

[0034] Based on the real-time disease tracking records, the professional opinions of the expert system are introduced, and the intelligent optimization algorithm is used to comprehensively evaluate and adjust the preliminary treatment plan, considering the effects and potential risks of different treatment measures, and generating optimized treatment recommendations;

[0035] Utilizing the optimized treatment recommendations and combining them with the comprehensive support functions of the telemedicine monitoring platform, a telemedicine support and treatment plan is ultimately determined.

[0036] Optionally, based on the remote medical support and treatment plan, the optimal transfer route to the nearest port or island with medical facilities is dynamically planned, taking into account legal constraints in international waters, the possibility of medical support along the way and the urgency of the patient's condition, to generate a detailed dispatch action plan, including:

[0037] Using the remote medical support and treatment plan, combined with the patient's real-time condition and required medical resources, the optimal transfer destination is preliminarily screened to obtain a list of candidate transfer destinations;

[0038] Based on the list of candidate transshipment destinations, the legal constraints in international waters, the possibility of medical support along the way, and the urgency of the patient's condition are integrated, and a multi-factor comprehensive evaluation model is applied to quantitatively evaluate the accessibility and safety of each candidate destination to generate a destination evaluation report;

[0039] Based on the destination assessment report, the optimal route from the current location to each candidate destination is calculated and processed using a dynamic path planning algorithm, combined with real-time traffic flow data analysis, weather forecast services, and on-site safety risk assessment to obtain an initial path solution set;

[0040] Utilizing the initial path plan set, the possible direction and speed of the accident spread are simulated through the emergency impact range expansion technology, and the safety of the path is further predicted and processed to obtain the optimal transfer route. Combined with the remote medical support and treatment plan, a detailed scheduling action plan is formed.

[0041] In a second aspect, an embodiment of the present application provides a system for implementing real-time medical response and dispatch at sea based on adaptive satellite and ground network switching, including:

[0042] A receiving module is used to receive emergency medical assistance signals from offshore vessels or platforms through an adaptively selected satellite communication network or a ground 5G network, receive emergency medical assistance signals from offshore vessels or platforms, process and obtain precise geographic coordinates of the assistance location, environmental conditions and preliminary patient diagnosis information, and generate a comprehensive report on emergency medical events;

[0043] An evaluation module is used to evaluate the time and feasibility of different marine medical rescue resources arriving at the place of help based on the comprehensive report of the emergency medical incident, combined with dynamic meteorological data of the sea area and ocean current forecasts, and apply an intelligent resource matching algorithm, analyze the influence of weather changes and sea conditions through the sensitivity analysis technology of influencing factors, ensure that the selected medical response unit operates efficiently under various conditions, and obtain the most suitable medical response unit;

[0044] An analysis module is used to establish a high-definition video connection between the scene of the call for help and the land medical center using a two-way satellite link based on the most suitable medical response unit, and introduce a remote medical decision-making support system, adopt a disease progression prediction algorithm, analyze and process the historical case database and real-time physiological parameter monitoring data, provide accurate treatment suggestions and guidance, and obtain remote medical support and treatment plans;

[0045] The planning module is used to dynamically plan the optimal transfer route to the nearest port or island with medical facilities based on the remote medical support and treatment plan, taking into account the legal constraints of international waters, the possibility of medical support along the way and the urgency of the patient's condition, and generate a detailed scheduling action plan.

[0046] In a third aspect, an embodiment of the present application provides a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for real-time response and scheduling of medical services at sea based on adaptive satellite and ground network switching as described in the first aspect.

[0047] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program. When the computer program is executed by a computer, a method for achieving real-time response and scheduling of medical services at sea based on adaptive switching between satellite and ground networks as described in the first aspect is implemented.

[0048] In the embodiment of the present application, an emergency medical help signal from a ship or platform at sea is transmitted through an adaptively selected satellite communication network or a ground 5G network, and the precise geographic coordinates, environmental conditions and preliminary diagnosis information of the help location are processed and obtained to generate a comprehensive report on emergency medical events. According to the comprehensive report on emergency medical events, combined with dynamic meteorological data of the sea area and ocean current prediction, an intelligent resource matching algorithm is applied to evaluate the time and feasibility of different marine medical rescue resources arriving at the help location, and the influence of weather changes and sea conditions is analyzed through the influencing factor sensitivity analysis technology to ensure that the selected medical response unit operates efficiently under various conditions and obtain the most suitable medical response unit. Based on the most suitable medical response unit, a high-definition video connection between the help site and the land medical center is established using a two-way satellite link, and a telemedicine decision-making assistance system is introduced. The disease progression prediction algorithm is used to analyze and process the historical case library and real-time physiological parameter monitoring data, provide accurate treatment suggestions and guidance, and obtain telemedicine support and treatment plans. Based on the telemedicine support and treatment plan, the optimal transfer route to the nearest port or island with medical facilities is dynamically planned and processed, and a detailed scheduling action plan is generated by considering the legal constraints of international waters, the possibility of medical support along the way, and the urgency of the patient's condition.

[0049] The technical solution of this application has the following beneficial effects:

[0050] This method significantly improves the speed and accuracy of medical emergency response at sea, ensuring the effective deployment and efficient operation of medical resources. Through real-time data transmission and telemedicine support, the effect of medical treatment is enhanced and the risk of delay is reduced. At the same time, the path planning and resource selection are comprehensively considered to optimize the entire rescue process, improve the success rate of rescue operations and the survival rate of patients. In addition, this method also ensures transparency and traceability in the rescue process, providing a scientific basis for subsequent evaluation and improvement.

[0051] Furthermore, this method significantly improves the speed and accuracy of maritime medical emergency response, ensuring the effective deployment and efficient operation of medical resources. Through intelligent resource matching and dynamic evaluation, the response time is shortened and the risk of delay is reduced. At the same time, the multi-stage evaluation and review process ensures that the selected medical response unit can not only quickly reach the place of help under the current conditions, but also maintain efficient operation in various complex environments. In addition, the impact of weather changes and sea conditions is fully considered, which enhances the reliability and success rate of rescue operations, provides patients with the best medical protection, and greatly improves the success rate of rescue operations and the survival rate of patients.

[0052] Furthermore, this method significantly improves the quality and efficiency of medical emergency response at sea, ensuring that patients can receive timely and accurate medical treatment. Through high-definition video connection and two-way satellite link technology, stable and low-latency communication between the scene of help and the land medical center is achieved, allowing medical experts to intuitively understand the patient's condition and provide real-time guidance, greatly enhancing the support effect of telemedicine. At the same time, the introduction of telemedicine decision-making support systems and the application of disease progression prediction algorithms provide scientific and personalized treatment recommendations, ensuring the accuracy and effectiveness of treatment plans. In addition, the use of intelligent optimization algorithms further improves the flexibility and adaptability of treatment plans, ensuring that they can adapt to changing medical needs, provide patients with the best medical protection, and greatly improve the success rate of rescue operations and the survival rate of patients.

[0053] These and other aspects of the present application will become more clearly understood in the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0055] Figure 1 A flowchart of a method for implementing real-time medical response and scheduling at sea based on adaptive satellite and ground network switching provided in an embodiment of the present application;

[0056] Figure 2 A schematic diagram of the structure of a system for implementing real-time medical response and dispatch at sea based on adaptive satellite and ground network switching provided in an embodiment of the present application;

[0057] Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0058] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0059] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be performed in the order in which they appear in this article or may be performed in parallel. In addition, these processes may include more or fewer operations, and these operations may be performed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., and do not represent the order of precedence, nor do they limit "first" and "second" to be different types.

[0060] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0061] Figure 1 A flowchart of a method for implementing real-time response and scheduling of medical services at sea based on adaptive satellite and ground network switching is provided for an embodiment of the present application. Figure 1 As shown, the method includes:

[0062] Through adaptively selected satellite communication networks or ground 5G networks, emergency medical assistance signals from offshore vessels or platforms are processed and obtained, including precise geographic coordinates of the assistance location, environmental conditions, and preliminary patient diagnosis information, to generate a comprehensive report on emergency medical events;

[0063] In this step, the emergency medical help signal from the offshore vessel or platform is processed and obtained through the adaptively selected satellite communication network or ground 5G network, with the precise geographic coordinates of the help location, environmental conditions and preliminary patient diagnosis information, to generate a comprehensive emergency medical incident report. Specifically, the location data (such as GPS coordinates), environmental conditions (such as weather conditions, sea conditions) and preliminary patient diagnosis information (such as symptom description, vital signs) contained in the help signal are used to generate a detailed comprehensive emergency medical incident report.

[0064] In the embodiment of the present application, the emergency medical assistance signal from the ship or platform at sea is received in real time through the adaptively selected satellite communication network or the ground 5G network, and the signal content is analyzed by the dedicated software to extract the precise geographic coordinates of the location for assistance, environmental conditions and preliminary diagnosis information of the patient. Subsequently, the system automatically generates a comprehensive report on the emergency medical incident, providing detailed basic data support for subsequent rescue operations.

[0065] Suppose a crew member on a distant-water fishing vessel in the North Pacific Ocean has an emergency with a heart attack. The crew uses the satellite phone on board to send an emergency medical assistance signal, which contains the GPS coordinates of the fishing vessel, current weather conditions (such as wind speed and wave height), and the patient's preliminary diagnosis information (such as abnormal heart rate and chest pain). After receiving the signal, the system immediately analyzes the signal content, extracts key data, and generates a detailed comprehensive report on the emergency medical incident. The report not only includes the precise geographic location and environmental conditions, but also includes the patient's preliminary condition assessment, providing comprehensive data support for subsequent rescue operations.

[0066] Based on the comprehensive report of the emergency medical incident, combined with the dynamic meteorological data of the sea area and the ocean current forecast, the intelligent resource matching algorithm is applied to evaluate the time and feasibility of different marine medical rescue resources arriving at the place of help, and the influence of weather changes and sea conditions is analyzed through the sensitivity analysis technology of influencing factors to ensure that the selected medical response unit operates efficiently under various conditions and obtain the most suitable medical response unit;

[0067] In this step, based on the comprehensive report of the emergency medical incident, combined with the dynamic meteorological data of the sea area and the ocean current forecast, the intelligent resource matching algorithm (SRMA) is applied to evaluate the time and feasibility of different marine medical rescue resources to reach the place of help, and the influence of weather changes and sea conditions is analyzed through the sensitivity analysis technology of influencing factors (SAF) to ensure that the selected most suitable medical response unit operates efficiently under various conditions. The dynamic meteorological data and ocean current forecast in this step are used to optimize the path planning, while the intelligent resource matching algorithm is used to evaluate the accessibility and safety of each resource.

[0068] In the embodiment of the present application, based on the comprehensive report of emergency medical events, the real-time dynamic meteorological data of the sea area and the ocean current forecast are integrated, and the intelligent resource matching algorithm is applied to evaluate the various marine medical rescue resources. At the same time, the influence of weather changes and sea conditions on the rescue operation is analyzed through the sensitivity analysis technology of influencing factors, and the most suitable medical response unit is finally determined to ensure that it can operate efficiently under various conditions.

[0069] Assume that after the above-mentioned distant-water fishing vessel issued an emergency request for help, the system generated a comprehensive report on the emergency medical incident. Next, the system combines the dynamic meteorological data of the current sea area (such as wind direction, wind speed, wave height, etc. in the next 24 hours) and ocean current forecasts to evaluate all available medical rescue resources nearby (such as nearby medical ships, helicopters, Coast Guard, etc.). The intelligent resource matching algorithm calculates the time and feasibility of each resource arriving at the fishing boat, taking into account the impact of weather changes and sea conditions. After analysis, the system selected the nearest fully equipped medical ship as the most suitable medical response unit because it can not only arrive within the expected time, but also adapt to the upcoming severe weather conditions, ensuring the safety and efficiency of the rescue operation.

[0070] Optionally, the comprehensive report on the emergency medical incident, combined with dynamic meteorological data of the sea area and ocean current forecasts, applies an intelligent resource matching algorithm to evaluate the time and feasibility of different marine medical rescue resources arriving at the place of help, analyzes the impact of weather changes and sea conditions through influencing factor sensitivity analysis technology, ensures that the selected medical response unit operates efficiently under various conditions, and obtains the most suitable medical response unit, including:

[0071] Using the comprehensive report on emergency medical incidents, a preliminary evaluation is conducted on the location information of different maritime medical rescue resources and their accessibility and transportation safety to obtain a preliminary response effectiveness evaluation; based on the preliminary response effectiveness evaluation, combined with dynamic meteorological data of the sea area and ocean current forecasts, an intelligent resource matching algorithm is applied to quantitatively evaluate the time and feasibility of each medical rescue resource arriving at the place of help, and generate a medical rescue resource evaluation result; based on the medical rescue resource evaluation result, the influencing factor sensitivity analysis technology is used to conduct an in-depth analysis of weather changes and sea conditions to obtain an influencing factor analysis report; using the influencing factor analysis report, a final review is conducted on the operating efficiency of each medical rescue resource under different conditions to ensure that the selected medical response unit can operate efficiently under various conditions and obtain the most suitable medical response unit.

[0072] In this step, according to the comprehensive report of the emergency medical incident, combined with the dynamic meteorological data of the sea area and the ocean current forecast, the intelligent resource matching algorithm (SRMA) is applied to evaluate the time and feasibility of different marine medical rescue resources to reach the place of help, and the influence of weather changes and sea conditions is analyzed through the sensitivity analysis technology of influencing factors (SAF) to ensure that the selected most suitable medical response unit operates efficiently under various conditions. Specifically, the preliminary evaluation process includes analyzing the location information of different marine medical rescue resources and their accessibility and transportation safety to obtain a preliminary response effectiveness evaluation; the quantitative evaluation process is based on the preliminary response effectiveness evaluation, combined with the dynamic meteorological data of the sea area and the ocean current forecast, and the intelligent resource matching algorithm is applied to generate the medical rescue resource evaluation results; the deep analysis process uses the sensitivity analysis technology of influencing factors to conduct a detailed analysis of weather changes and sea conditions to obtain an influencing factor analysis report; the final review process is based on the influencing factor analysis report to evaluate the operating efficiency of each medical rescue resource under different conditions to ensure that the selected medical response unit can operate efficiently under various conditions.

[0073] In the embodiment of the present application, firstly, the comprehensive report of emergency medical events is used to conduct a preliminary assessment of the location information, accessibility, and transportation safety of different maritime medical rescue resources to obtain a preliminary response efficiency evaluation; secondly, based on the preliminary response efficiency evaluation, combined with the dynamic meteorological data of the sea area and ocean current forecasts, an intelligent resource matching algorithm is used to quantitatively evaluate the time and feasibility of each medical rescue resource arriving at the place of help, and generate a medical rescue resource assessment result; thirdly, based on the medical rescue resource assessment result, the influencing factor sensitivity analysis technology is used to conduct an in-depth analysis of weather changes and sea conditions to obtain an influencing factor analysis report; finally, the influencing factor analysis report is used to conduct a final review of the operating efficiency of each medical rescue resource under different conditions to ensure that the selected medical response unit can operate efficiently under various conditions and obtain the most suitable medical response unit.

[0074] Suppose a crew member is seriously injured on a cargo ship in the middle of the Atlantic Ocean, and the crew sends an emergency medical assistance signal using a satellite phone. After receiving the signal, the system immediately generates a detailed comprehensive report on the emergency medical incident; then, the system first conducts a preliminary assessment of the location information of all available medical rescue resources nearby (such as medical ships, helicopters, Coast Guard, etc.), as well as their accessibility and transportation safety, and obtains a preliminary response effectiveness evaluation; secondly, based on the preliminary response effectiveness evaluation, the system combines the dynamic meteorological data of the current sea area (such as wind direction, wind speed, wave height, etc. in the next 24 hours) and ocean current forecasts, and applies an intelligent resource matching algorithm to calculate the time and feasibility of each resource arriving at the cargo ship, and generates a medical rescue resource evaluation result; thirdly, based on the medical rescue resource evaluation result, the system uses the influencing factor sensitive The system used in-depth analysis technology to analyze weather changes and sea conditions, and obtained an analysis report on influencing factors. Finally, the system used the influencing factor analysis report to conduct a final review of the operating efficiency of various medical rescue resources under different conditions to ensure that the selected medical response unit can operate efficiently under various conditions. Finally, a fully equipped medical ship was selected as the most suitable medical response unit because it can not only arrive within the expected time, but also adapt to the upcoming severe weather conditions, ensuring the safety and efficiency of the rescue operation. Through the above steps, the system provided a scientific and reasonable resource scheduling plan for this emergency medical incident at sea, ensuring that patients can receive timely and efficient treatment.

[0075] Optionally, based on the medical rescue resource assessment result, the influencing factor sensitivity analysis technology is used to perform in-depth analysis and processing on weather changes and sea conditions to obtain an influencing factor analysis report, including:

[0076] Using the medical rescue resource assessment results, data on weather changes and sea conditions are collected and processed to generate an original influencing factor data set; based on the original influencing factor data set, a multi-factor comprehensive assessment model is applied to quantitatively analyze the importance of each factor and their interrelationships to generate a factor importance score sheet; based on the factor importance score sheet, combined with successful experiences and lessons from historical rescue cases, the potential impact of each influencing factor is deeply analyzed to obtain influencing factor analysis results; the influencing factor analysis results are integrated to form a comprehensive influencing factor analysis report.

[0077] Optionally, the influencing factor analysis report is used to conduct a final review of the operating efficiency of each medical rescue resource under different conditions to ensure that the selected medical response unit can operate efficiently under various conditions and obtain the most suitable medical response unit, including:

[0078] Using the influencing factor analysis report, the operational efficiency of each medical rescue resource under different weather conditions and sea conditions is quantitatively evaluated to obtain an operational efficiency score; based on the operational efficiency score and in combination with successful experiences and lessons in the historical rescue case library, the adaptability and reliability of each medical rescue resource are comprehensively evaluated to generate a medical rescue resource adaptability report; based on the medical rescue resource adaptability report, a multi-dimensional performance optimization algorithm is applied to conduct a final review of the overall performance of each medical rescue resource to determine the optimal medical response unit; the optimal medical response unit is confirmed to ensure that it can operate efficiently under various conditions, and ultimately the most suitable medical response unit is generated.

[0079] In this step, based on the medical rescue resource assessment results, the influencing factor sensitivity analysis technology (SAF) is used to deeply analyze the weather changes and sea conditions to obtain an influencing factor analysis report. Specifically, the original influencing factor data set includes data on weather changes and sea conditions collected from the medical rescue resource assessment results, which are used to generate a factor importance score table; the multi-factor comprehensive evaluation model is used to quantitatively analyze the importance and interrelationships of each factor; the factor importance score table combines the successful experiences and lessons learned from historical rescue cases to deeply analyze the potential impact of each influencing factor to obtain the influencing factor analysis results; and finally integrates these analysis results to form a comprehensive influencing factor analysis report. In addition, the influencing factor analysis report is used to conduct a final review of the operating efficiency of each medical rescue resource under different conditions to ensure that the selected medical response unit can operate efficiently under various conditions. Specifically, the operational efficiency score is the result of a quantitative assessment of the operational efficiency of each medical rescue resource under different weather conditions and sea conditions; the medical rescue resource adaptability report is the result of a comprehensive evaluation of the adaptability and reliability of each medical rescue resource based on the operational efficiency score combined with the lessons learned from the historical rescue case library; by applying a multi-dimensional performance optimization algorithm, the overall performance of each medical rescue resource is finally reviewed and processed to determine the optimal medical response unit and confirm its ability to operate efficiently under various conditions.

[0080] In the embodiment of the present application, firstly, the data of weather changes and sea conditions are collected and processed using the medical rescue resource assessment results to generate an original influencing factor data set; secondly, based on the original influencing factor data set, a multi-factor comprehensive assessment model is applied to quantitatively analyze the importance of each factor and their interrelationships to generate a factor importance score table; thirdly, based on the factor importance score table and in combination with the successful experiences and lessons learned from historical rescue cases, the potential impact of each influencing factor is deeply analyzed to obtain influencing factor analysis results; finally, the influencing factor analysis results are integrated to form a comprehensive influencing factor analysis report. Next, the influencing factor analysis report is used to conduct a quantitative evaluation of the operational efficiency of each medical rescue resource under different weather conditions and sea conditions to obtain an operational efficiency score; based on the operational efficiency score and in combination with the successful experiences and lessons learned in the historical rescue case library, a comprehensive evaluation is conducted on the adaptability and reliability of each medical rescue resource to generate a medical rescue resource adaptability report; based on the medical rescue resource adaptability report, a multi-dimensional performance optimization algorithm is applied to conduct a final review of the overall performance of each medical rescue resource to determine the optimal medical response unit; the optimal medical response unit is confirmed to ensure that it can operate efficiently under various conditions, and ultimately the most suitable medical response unit is generated.

[0081] Assume that a crew member of a fishing boat in the South China Sea is seriously injured. After receiving the distress signal, the system immediately generates a comprehensive report on the emergency medical incident. Subsequently, the system conducts a preliminary assessment of all available medical rescue resources in the vicinity and obtains a preliminary response efficiency evaluation. Next, the system combines the dynamic meteorological data of the sea area and the ocean current forecast, and applies the intelligent resource matching algorithm to calculate the time and feasibility of each resource reaching the fishing boat, and generates a medical rescue resource evaluation result. Then, the system first uses the medical rescue resource evaluation result to collect and process the data on weather changes and sea conditions to generate an original influencing factor data set. Secondly, based on the original influencing factor data set, the multi-factor comprehensive evaluation model is applied to quantitatively analyze the importance and mutual relationship of each factor to generate a factor importance score table. Thirdly, based on the factor importance score table, combined with the successful experience and lessons learned in historical rescue cases, the potential impact of each influencing factor is deeply analyzed and processed to obtain the impact factor. the results of the influencing factor analysis; finally, the results of the influencing factor analysis are integrated to form a comprehensive influencing factor analysis report; then, the system uses the influencing factor analysis report to quantitatively evaluate the operational efficiency of each medical rescue resource under different weather conditions and sea conditions, and obtains an operational efficiency score; based on the operational efficiency score, combined with the successful experiences and lessons in the historical rescue case library, the adaptability and reliability of each medical rescue resource are comprehensively evaluated and processed to generate a medical rescue resource adaptability report; based on the medical rescue resource adaptability report, a multi-dimensional performance optimization algorithm is applied to conduct a final review of the overall performance of each medical rescue resource to determine the optimal medical response unit; the optimal medical response unit is confirmed to ensure that it can operate efficiently under various conditions, and finally the most suitable medical response unit is generated; through the above steps, the system provides a scientific and reasonable resource scheduling plan for this maritime emergency medical incident to ensure that patients can receive timely and efficient treatment.

[0082] This application takes into account that in the prior art, the scheduling of medical rescue resources at sea has problems such as long response time, inaccurate evaluation, and lack of sufficient consideration of dynamic environmental factors. Traditional methods usually schedule resources based on static data and empirical rules, which cannot effectively cope with complex changes in the marine environment and changeable weather conditions, resulting in low rescue efficiency. Therefore, the embodiment of the present invention proposes a more sophisticated and intelligent medical rescue resource assessment scheme, which aims to solve the above technical problems, improve the speed and accuracy of rescue operations, and ensure that the selected medical response unit can operate efficiently under various conditions.

[0083] Optionally, the preliminary response effectiveness evaluation is combined with the dynamic meteorological data of the sea area and the ocean current forecast, and an intelligent resource matching algorithm is applied to quantitatively evaluate the time and feasibility of each medical rescue resource arriving at the help-seeking location, and generate a medical rescue resource evaluation result, including:

[0084] When calculating the estimated time T for medical rescue resources to arrive at the place of help, arrival Previously, it was necessary to comprehensively evaluate the on-site information and generate a comprehensive report on emergency medical incidents. Multi-source data fusion technology was used to enrich the report content, and combined with real-time dynamic sea weather data and ocean current forecasts, an intelligent resource matching algorithm was used to conduct a preliminary assessment of different marine medical rescue resources, providing basic data for subsequent arrival time calculations.

[0085]

[0086] Among them, t arrival represents the estimated time for medical rescue resources to arrive at the place of help; d is the distance from the current location of medical resources to the place of help; V eff (W,C,M) is the effective speed after considering the weather change factor W, the sea condition change factor C and the ship maneuverability factor M; α(W) is the weather influence coefficient adjusted according to the real-time meteorological conditions; W is the influence factor of weather change on the navigation speed; β(C) is the sea condition influence coefficient adjusted according to the real-time ocean current forecast; C is the influence factor of sea condition change on the navigation speed; η(T current ) is based on the current time T current The adjusted time sensitivity factor reflects the impact of different time periods on the arrival time; ψ(H history ) is the average delay time in similar situations in the historical rescue case database; H history is the relevant data in the historical rescue case database; ζ(S seasonal ) is the seasonal factor affecting the sailing speed; S seasonal is the current seasonal sailing condition; χ(F fuel ) is the factor affecting the remaining fuel on the sailing speed; F fuel is the remaining amount of fuel for current medical rescue resources;

[0087] After calculating T arrival Finally, the legal constraints of international waters, the possibility of medical support along the way, and the urgency of the patient's condition were integrated, and a multi-factor comprehensive evaluation model was applied to quantify the accessibility and safety of each candidate destination. The emergency impact range expansion technology and path safety assessment method were introduced to simulate the direction and speed of accident diffusion, and further predict the path safety to calculate S feasibility Provide necessary input;

[0088]

[0089] Among them, S feasibility represents the feasibility score of medical rescue resources; γ is the time impact weight factor, which is used to adjust the impact of arrival time on the score; λ is the time at the place of help; T threshold is the maximum acceptable arrival time threshold; δ is the risk impact weight factor, which is used to adjust the impact of security risk on the score; R risk is the risk score obtained from the on-site safety risk assessment; R max is the maximum possible security risk score; θ(P priority ) is based on the task priority P priority Adjusted priority impact coefficient; P priority is the priority weight of the rescue mission, reflecting the importance and urgency of the mission; φ(D distance ) is the distance penalty factor, based on the distance D from the current medical resource location to the help-seeking location distance , feasibility score for reducing long-distance rescue;

[0090] After calculating S feasibility After that, combined with the real-time feedback of the telemedicine support platform Based on the professional opinions of the expert system, the initial treatment plan is adjusted through an intelligent optimization algorithm to ensure that it adapts to the ever-changing medical needs; ultimately, a comprehensive and flexible medical rescue resource assessment result is formed to provide a scientific basis for actual scheduling and ensure the successful implementation of the rescue operation.

[0091] This formula is designed to accurately evaluate the time and feasibility of different medical rescue resources arriving at the place of help, and introduces two key formulas: T arrival and S feasibility The former is used to calculate the estimated time of arrival, and the latter is used to quantify the accessibility and safety of each candidate destination. The introduction of these formulas makes it possible to comprehensively consider multiple influencing factors (such as weather, sea conditions, ship maneuverability, etc.), and optimize resource allocation through a multi-factor comprehensive evaluation model to ensure the successful implementation of the rescue operation.

[0092] The following is a brief introduction to the design reasons of each sub-item of the formula:

[0093]

[0094] Distance D: represents the distance from the current medical resource location to the place where help is sought; this is the basic parameter for calculating the arrival time; effective speed v eff(W,C,M): The effective speed after considering the weather change factor W, the sea state change factor C and the ship maneuverability factor M; this reflects the speed attenuation during actual navigation; Weather impact adjustment α(W)·W: The weather impact coefficient adjusted according to real-time meteorological conditions multiplied by the impact factor of weather changes on navigation speed; used to quantify the impact of weather on navigation speed; Sea state impact adjustment β(C)·C: The sea state impact coefficient adjusted according to real-time ocean current forecasts multiplied by the impact factor of sea state changes on navigation speed; used to quantify the impact of sea conditions on navigation speed; Time sensitivity adjustment η(T current ): According to the current time T current Adjusted time sensitivity factor; reflects the impact of different time periods on arrival time; historical delay time ψ(H history ): Average delay time in similar situations in the historical rescue case database; used to correct the arrival time estimate; seasonal effect adjustment ζ(S seasonal ): seasonal factors affecting the sailing speed; used to consider the impact of seasonal changes on the sailing speed; fuel remaining amount affects the adjustment χ(F fuel ): The factor affecting the remaining fuel on the sailing speed; used to consider the impact of the fuel level on the sailing speed;

[0095] The following is a brief introduction to how to obtain the parameters of the formula:

[0096] D: obtained through geographic information system (GIS); V eff(W,C,M) : calculated through ship performance database and real-time meteorological and ocean current data; α(W) and W: obtained through meteorological forecast service; β(C) and C: obtained through ocean current prediction model; η(T current ): Based on the real-time clock system; ψ(H history ): extracted from the historical database; ζ(S seasonal ): Obtained from the statistical data of the current season; χ(F fuel ) and F fuel : Obtained through the shipboard fuel monitoring system;

[0097] The following is a brief introduction to the design reasons of each sub-item of the formula:

[0098]

[0099] Arrival time impact The time impact weight factor multiplied by the exponential decay function is used to quantify the impact of arrival time on the score; safety risk impact The risk impact weight factor multiplied by the ratio of the security risk score to the maximum possible risk score is used to quantify the impact of the security risk on the score; the priority impact θ(P priority )·P priority: Priority impact coefficient multiplied by the task priority weight is used to quantify the impact of task importance and urgency on the score; distance penalty -φ(D distance ): distance penalty factor, used to reduce the feasibility score of long-distance rescue;

[0100] The following is a brief introduction to how to obtain the parameters of the formula:

[0101] γ and λ: set based on the importance and urgency of the task; T threshold : Set according to task requirements; R risk and R max : obtained through the on-site safety risk assessment tool; δ: set based on safety standards; φ(D distance ) and D distance : Obtained through geographic information system;

[0102] Suppose a crew member is seriously injured on a merchant ship in the middle of the Atlantic Ocean. After receiving the distress signal, the system first generates a comprehensive report on the emergency medical incident and enriches the report content through multi-source data fusion technology. Next, the system combines real-time dynamic weather data and ocean current forecasts in the sea area, and applies intelligent resource matching algorithms to conduct a preliminary assessment of all available medical rescue resources nearby, and obtains a preliminary response effectiveness evaluation. For example, for a medical ship:

[0103]

[0104] T arrival =15 hours

[0105] Then, the system integrates the legal constraints of international waters, the possibility of medical support along the way, and the urgency of the patient's condition, and applies a multi-factor comprehensive evaluation model to quantify the accessibility and safety of each candidate destination, such as:

[0106]

[0107] S feasibility =0.7

[0108] Finally, the system combines the real-time feedback from the telemedicine support platform and the professional opinions of the expert system, and adjusts the initial treatment plan through an intelligent optimization algorithm to ensure that it adapts to the changing medical needs. Finally, a comprehensive and flexible medical rescue resource assessment result is formed, which provides a scientific basis for actual dispatch and ensures the successful implementation of the rescue operation. Assuming that the threshold is set to T threshold = 10 hours, due to T arrival =15hours is greater than the set threshold, which indicates that this medical ship is feasible but not the best choice. The system continues to evaluate other resources until the optimal solution is found.

[0109] Through the above steps, the system not only improves the scientificity and reliability of rescue decisions, but also ensures the safety and timeliness of the rescue path, greatly improving the success rate of rescue operations and the patient's chance of survival.

[0110] Based on the most suitable medical response unit, a high-definition video connection is established between the scene of the call for help and the land medical center using a two-way satellite link, and a remote medical decision-making support system is introduced. The disease progression prediction algorithm is used to analyze and process the historical case database and real-time physiological parameter monitoring data to provide accurate treatment suggestions and guidance, and obtain remote medical support and treatment plans;

[0111] In this step, based on the most suitable medical response unit, a high-definition video connection is established between the scene of the call for help and the land medical center using a two-way satellite link, and a telemedicine decision support system (TADS) is introduced. The disease progression prediction algorithm (CPPA) is used to analyze and process the historical case database and real-time physiological parameter monitoring data, provide accurate treatment suggestions and guidance, and obtain telemedicine support and treatment plans. The high-definition video connection ensures stable and low-latency communication quality, while the telemedicine decision support system provides professional medical guidance.

[0112] In the embodiment of the present application, a high-definition video connection is established between the help-seeking site and the land medical center through a two-way satellite link, so as to realize real-time interaction between the help-seeking site and medical experts. At the same time, a remote medical decision-making support system is introduced, and the disease progression prediction algorithm is used to analyze the historical case library and real-time physiological parameters to generate a personalized preliminary treatment plan, which is adjusted through an intelligent optimization algorithm to finally obtain remote medical support and treatment plans.

[0113] Assuming that the selected medical vessel is equipped with a two-way satellite link device, a high-definition video connection is established between the scene of the call for help and the land medical center during the approach to the fishing boat. Medical experts on land can visually observe the patient's condition through the video connection and monitor the patient's physiological parameters (such as electrocardiogram, blood pressure, and blood oxygen saturation) in real time. The remote medical decision-making support system combines similar cases in the historical case library and real-time physiological parameter monitoring data, applies the disease progression prediction algorithm, and provides personalized preliminary treatment plans. For example, the system recommends that patients be given nitroglycerin immediately to relieve the burden on the heart and continuously monitor heart rate changes. Based on these instructions, medical experts guide the medical staff on board to implement first aid measures through video connections to ensure that patients receive the best medical protection during transportation.

[0114] Optionally, the most suitable medical response unit uses a two-way satellite link to establish a high-definition video connection between the help-seeking site and the land medical center, and introduces a remote medical decision-making support system, adopts a disease progression prediction algorithm, analyzes and processes the historical case database and real-time physiological parameter monitoring data, provides accurate treatment suggestions and guidance, and obtains remote medical support and treatment plans, including:

[0115] By using the most suitable medical response unit, combined with high-precision positioning technology and two-way satellite link technology, the high-definition video connection between the help-seeking site and the land medical center is configured and optimized to ensure stable, low-latency communication quality and obtain high-definition video connection support; based on the high-definition video connection support, a remote medical decision-making support system is introduced, integrating two-way video consultation and disease tracking functions, realizing real-time interaction and guidance between the help-seeking site and land medical experts, and generating a comprehensive remote medical monitoring platform; based on the remote medical monitoring platform, a disease progression prediction algorithm is applied to comprehensively analyze and process similar cases in the historical case library and real-time physiological parameter monitoring data at the help-seeking site, and combined with the patient's personalized factors, accurate treatment suggestions and guidance are provided to generate a personalized preliminary treatment plan; using the personalized preliminary treatment plan, combined with the real-time feedback provided by the remote medical monitoring platform and the professional opinions of the expert system, comprehensive evaluation and adjustment are carried out through an intelligent optimization algorithm to obtain remote medical support and treatment plans.

[0116] In this step, based on the most suitable medical response unit, a high-definition video connection is established between the help-seeking site and the land medical center using a two-way satellite link, and a telemedicine decision support system (TADS) is introduced. The disease progression prediction algorithm (CPPA) is used to analyze and process the historical case library and real-time physiological parameter monitoring data, provide accurate treatment suggestions and guidance, and obtain telemedicine support and treatment plans. Specifically, the high-definition video connection support includes combining high-precision positioning technology and two-way satellite link technology to ensure stable and low-latency communication quality; the telemedicine monitoring platform integrates two-way video consultation and disease tracking functions to achieve real-time interaction and guidance between the help-seeking site and land medical experts; the personalized initial treatment plan is based on the telemedicine monitoring platform, and the disease progression prediction algorithm is used to comprehensively analyze and process similar cases in the historical case library and real-time physiological parameter monitoring data at the help-seeking site; the telemedicine support and treatment plan is comprehensively evaluated and adjusted through an intelligent optimization algorithm combined with the real-time feedback provided by the telemedicine monitoring platform and the professional opinions of the expert system.

[0117] In the embodiment of the present application, firstly, the most suitable medical response unit is used, combined with high-precision positioning technology and two-way satellite link technology, to configure and optimize the high-definition video connection between the help-seeking site and the land medical center, to ensure stable, low-latency communication quality, and to obtain high-definition video connection support; secondly, based on the high-definition video connection support, a remote medical decision-making support system is introduced, integrating two-way video consultation and disease tracking functions, to achieve real-time interaction and guidance between the help-seeking site and land medical experts, and to generate a comprehensive remote medical monitoring platform; thirdly, based on the remote medical monitoring platform, a disease progression prediction algorithm is applied to comprehensively analyze and process similar cases in the historical case library and real-time physiological parameter monitoring data at the help-seeking site, and combined with the patient's personalized factors, accurate treatment suggestions and guidance are provided to generate a personalized preliminary treatment plan; finally, the personalized preliminary treatment plan is used, combined with the real-time feedback provided by the remote medical monitoring platform and the professional opinions of the expert system, and comprehensive evaluation and adjustment are performed through an intelligent optimization algorithm to obtain remote medical support and treatment plans.

[0118] Suppose a scientist on a research vessel in an area of ​​the Indian Ocean suddenly develops an acute illness. The ship is equipped with advanced medical equipment and two-way satellite links. After receiving the distress signal, the system selects the nearest fully equipped medical ship as the most suitable medical response unit; first, the technicians on the medical ship quickly configure and optimize the high-definition video connection between the scene of the distress and the land medical center by combining high-precision positioning technology and two-way satellite link technology, ensuring stable, low-latency communication quality, and providing high-definition video connection support for subsequent medical operations; secondly, the land medical center immediately launches the telemedicine decision-making support system, integrating two-way video consultation and disease tracking functions, realizing real-time interaction and guidance between the scene of the distress and land medical experts, and generating a comprehensive telemedicine monitoring platform; thirdly, based on this telemedicine monitoring platform , applying the disease progression prediction algorithm, comprehensively analyzing and processing similar cases in the historical case database and real-time physiological parameter monitoring data at the scene of help-seeking, combining personalized factors such as the patient's age, gender, and medical history, providing accurate treatment suggestions and guidance, and generating a personalized preliminary treatment plan; finally, using this preliminary treatment plan, combined with the real-time feedback provided by the telemedicine monitoring platform and the professional opinions of the expert system, a comprehensive evaluation and adjustment was carried out through the intelligent optimization algorithm, and finally a detailed telemedicine support and treatment plan was obtained; through the above steps, the system provided scientific and reasonable telemedicine support for this maritime emergency medical incident, ensuring that patients can receive timely and efficient treatment.

[0119] Optionally, the personalized preliminary treatment plan is used in combination with the real-time feedback provided by the telemedicine monitoring platform and the professional opinions of the expert system, and a comprehensive evaluation and adjustment is performed through an intelligent optimization algorithm to obtain telemedicine support and treatment plans, including:

[0120] Utilize the personalized preliminary treatment plan to estimate the patient's current condition and possible development trends, and generate a condition estimation report; based on the condition estimation report, combined with the high-definition video connection support and real-time physiological parameter monitoring data provided by the remote medical monitoring platform, continuously track and dynamically evaluate the patient's actual situation to obtain a real-time condition tracking record; based on the real-time condition tracking record, introduce the professional opinions of the expert system, apply the intelligent optimization algorithm to comprehensively evaluate and adjust the preliminary treatment plan, consider the effects and potential risks of different treatment measures, and generate optimized treatment recommendations; utilize the optimized treatment recommendations, combined with the comprehensive support functions of the remote medical monitoring platform, and ultimately determine the remote medical support and treatment plan.

[0121] In this step, the personalized preliminary treatment plan is used, combined with the real-time feedback provided by the telemedicine monitoring platform and the professional opinions of the expert system, and a comprehensive evaluation and adjustment is performed through an intelligent optimization algorithm to obtain a telemedicine support and treatment plan. Specifically, the condition prediction report includes the results of the estimated processing of the patient's current condition and possible development trends, which are used to guide subsequent treatment measures; the real-time condition tracking record is based on high-definition video connection support and real-time physiological parameter monitoring data, and the patient's actual situation is continuously tracked and dynamically evaluated. The optimized treatment recommendation is based on the real-time condition tracking record, introduces the professional opinions of the expert system, and uses the intelligent optimization algorithm to comprehensively evaluate and adjust the preliminary treatment plan. The finalized telemedicine support and treatment plan combines the comprehensive support functions of the telemedicine monitoring platform to ensure the scientific nature and personalization of the treatment plan.

[0122] In the embodiment of the present application, firstly, the personalized preliminary treatment plan is used to estimate the patient's current condition and possible development trends, and generate a condition estimation report; secondly, based on the condition estimation report, combined with the high-definition video connection support and real-time physiological parameter monitoring data provided by the remote medical monitoring platform, the patient's actual situation is continuously tracked and dynamically evaluated to obtain a real-time condition tracking record; thirdly, based on the real-time condition tracking record, the professional opinions of the expert system are introduced, and the preliminary treatment plan is comprehensively evaluated and adjusted using an intelligent optimization algorithm, taking into account the effects and potential risks of different treatment measures, to generate optimized treatment recommendations; finally, the optimized treatment recommendations are used, combined with the comprehensive support functions of the remote medical monitoring platform, to ultimately determine the remote medical support and treatment plan.

[0123] Suppose a researcher on a research vessel in the Arctic Ocean suddenly develops acute pneumonia. The ship is equipped with a two-way satellite link and basic medical equipment. After receiving the distress signal, the system selects the nearest fully equipped medical ship as the most suitable medical response unit; first, the technicians on the medical ship quickly configure and optimize the high-definition video connection between the distress site and the land medical center to ensure stable, low-latency communication quality; then, the land medical center activates the telemedicine decision-making support system and generates a personalized preliminary treatment plan; next, the system uses this preliminary treatment plan to estimate the patient's current condition (such as body temperature, respiratory rate, etc.) and possible development trends (such as the probability of worsening of the condition), and generates a detailed condition estimation report; based on the condition estimation report, the system combines the high-definition video connection support and real-time physiological parameter monitoring data provided by the telemedicine monitoring platform to estimate the patient's current condition (such as body temperature, respiratory rate, etc.) The actual situation was continuously tracked and dynamically evaluated, and detailed real-time disease tracking records were obtained; based on the real-time disease tracking records, the system introduced the professional opinions of the expert system, applied the intelligent optimization algorithm to comprehensively evaluate and adjust the preliminary treatment plan, considered the effects and potential risks of different treatment measures (such as antibiotic use, oxygen therapy), and generated optimized treatment recommendations; finally, the system used the optimized treatment recommendations, combined with the comprehensive support functions of the telemedicine monitoring platform, and finally determined the detailed telemedicine support and treatment plan to ensure that patients can obtain the best medical protection; through the above steps, the system provided scientific and reasonable telemedicine support for this maritime emergency medical incident, ensuring that patients can receive timely and efficient treatment.

[0124] This application takes into account that in the prior art, when providing treatment advice and guidance, telemedicine support systems often lack sufficient consideration of patient individual factors, resulting in inaccurate treatment plans. Traditional disease assessment methods mainly rely on static data and expert experience, and fail to make full use of real-time physiological parameter monitoring data and similar cases in the historical case library for comprehensive analysis, making the prediction of disease progression inaccurate. In addition, the effectiveness and potential risk assessments of different treatment measures are also relatively rough, making it difficult to adapt to complex and changing medical needs. Therefore, the embodiment of the present invention proposes a more sophisticated and intelligent personalized preliminary treatment plan generation method, which aims to solve the above-mentioned technical problems, improve the accuracy and personalization of treatment recommendations, and ensure that patients receive the best medical protection.

[0125] Optionally, based on the remote medical monitoring platform, the disease progression prediction algorithm is applied to comprehensively analyze and process similar cases in the historical case library and real-time physiological parameter monitoring data at the scene of help-seeking, and provide accurate treatment suggestions and guidance in combination with the patient's personalized factors, and generate a personalized preliminary treatment plan, including:

[0126] In calculating the disease progression score P after adjusting for personalized factors progress Previously, it was necessary to integrate the real-time physiological parameter monitoring data of the telemedicine monitoring platform with similar cases in the historical case database, and apply the disease progression prediction algorithm for comprehensive analysis; at the same time, it was necessary to consider the patient's personalized factors such as age and gender to provide detailed basic data for subsequent scoring;

[0127]

[0128] Among them, P progress represents the disease progression score after adjustment for personalized factors; According to the weight w i For similar cases H in the historical case database i and real-time physiological parameters R at the scene of help i The sum of the comprehensive scores; N is the number of cases or parameters; α(A) is the age effect coefficient adjusted according to the patient's age A; β(G) is the gender effect coefficient adjusted according to the patient's gender G; γ(C history ) is the overall impact factor of similar cases in the historical case database;

[0129] After calculating P progress Finally, the effects and potential risks of different treatment measures are evaluated in combination with the professional opinions of the expert system, and the time sensitivity factor is introduced to adjust the score according to the disease threshold; these transition steps comprehensively consider the disease progression, expert opinions and time urgency to generate a personalized preliminary treatment plan score S treatment ;

[0130]

[0131] Among them, S treatment represents the score of personalized initial treatment plan; δ(P progress ) is based on the disease progression score P progress Adjusted disease effect coefficient; E expert is the professional opinion score obtained from the expert system; ∈(E expert ) is the influence weight factor of professional opinion; φ(T thresh old) is based on the acceptable threshold of disease condition; T threshold is the time sensitivity factor of the adjustment; λ is the speed control parameter of the score decline when the condition deviates from the threshold;

[0132] After calculating S treatmentFinally, the scoring results are combined with the real-time feedback from the remote medical monitoring platform, and the initial treatment plan is comprehensively evaluated and adjusted through an intelligent optimization algorithm to ensure that it adapts to the ever-changing medical needs; ultimately, a comprehensive and flexible personalized initial treatment plan is formed to provide a scientific basis for actual treatment and ensure that patients receive the best medical protection.

[0133] The formula aims to provide more accurate and personalized treatment recommendations and introduces two key formulas: P progress and S treatment The former is used to calculate the disease progression score adjusted by personalized factors, and the latter is used to quantify the score of personalized initial treatment plan. The introduction of these formulas makes it possible to comprehensively consider the patient's personalized factors (such as age, gender), real-time physiological parameter monitoring data, and similar cases in the historical case library, conduct a comprehensive analysis through the disease progression prediction algorithm, and combine the professional opinions of the expert system to generate a scientific and reasonable personalized initial treatment plan.

[0134] The following is a brief introduction to the design reasons of each sub-item of the formula:

[0135]

[0136] Sum of comprehensive scores According to the weight w i For similar cases H in the historical case database i and real-time physiological parameters R at the scene of help i The sum of the comprehensive scores is used to quantify the overall situation of disease progression; Age effect adjustment α(A)·A: The age effect coefficient adjusted according to the patient's age A; used to consider the effect of age on disease progression; Gender effect adjustment β(G)·G: The gender effect coefficient adjusted according to the patient's gender G; used to consider the effect of gender on disease progression; The overall impact of historical cases γ(C history ): The overall impact factor of similar cases in the historical case database; used to enhance the generalization ability of the model;

[0137] The following is a brief introduction to how to obtain the parameters of the formula:

[0138] w i : obtained through machine learning model training; H i and R i : obtained from the historical case database and the remote medical monitoring platform; N: the number of cases or parameters; α(A) and A: obtained from demographic data; β(G) and G: obtained from demographic data; γ(C history ) and C history : Extracted from the historical case database;

[0139] The following is a brief introduction to the design reasons of each sub-item of the formula:

[0140]

[0141] The disease condition affected the adjusted δ(P progress )·P progress :According to the disease progression score P progress Adjusted disease impact coefficient; used to quantify the impact of disease progression on the score; expert opinion influence∈(E expert )·E expert : The influence weight factor of professional opinion is multiplied by the professional opinion score obtained from the expert system; used to quantify the impact of expert opinion on the score; time sensitivity adjustment According to the acceptable threshold of disease condition T threshold and the rating drop speed control parameter λ, introducing a time sensitivity factor to quantify the impact of time urgency on the rating;

[0142] The following is a brief introduction to how to obtain the parameters of the formula:

[0143] δ(P progress ) and P progress : Calculated by disease progression prediction algorithm; ∈(E expert ) and E expert :obtained through expert system; φ(T threshold ) and T threshold : set based on task requirements; λ: determined through experiments and simulations;

[0144] Suppose a scientist on a research vessel in the North Pacific suddenly develops acute pneumonia. After receiving the call for help, the system immediately activates the telemedicine decision-making support system and generates a comprehensive report on the emergency medical incident. Next, the system integrates the real-time physiological parameter monitoring data (such as body temperature and respiratory rate) of the telemedicine monitoring platform with similar cases in the historical case library (such as other acute pneumonia cases), and applies the disease progression prediction algorithm for comprehensive analysis. For example:

[0145]

[0146] P progress =0.86

[0147] Then, the system combines the professional opinions of the expert system to evaluate the effects and potential risks of different treatment measures, and introduces a time sensitivity factor to adjust the score according to the disease threshold. For example:

[0148]

[0149] S treatment =0.92

[0150] Finally, the system combines the scoring results with the real-time feedback from the remote medical monitoring platform, and uses an intelligent optimization algorithm to comprehensively evaluate and adjust the initial treatment plan, ultimately forming a comprehensive and flexible personalized initial treatment plan, which provides a scientific basis for actual treatment and ensures that patients receive the best medical care. Assume that the threshold is set to T threshold =0.8, due to P progress =0.86 is greater than the set threshold, which indicates that the patient's condition is more serious and more active treatment measures need to be taken as a priority.

[0151] Through the above steps, the system not only improves the accuracy and personalization of treatment recommendations, but also ensures that treatment plans can adapt to changing medical needs, greatly improving the success rate of rescue operations and the patient's chance of survival.

[0152] Based on the telemedicine support and treatment plan, the optimal transfer route to the nearest port or island with medical facilities is dynamically planned, taking into account the legal constraints of international waters, the possibility of medical support along the way and the urgency of the patient's condition, and generating a detailed scheduling action plan.

[0153] In this step, based on the telemedicine support and treatment plan, the optimal transfer route to the nearest port or island with medical facilities is dynamically planned, taking into account the legal constraints of international waters, the possibility of medical support along the way, and the urgency of the patient's condition, to generate a detailed dispatch action plan. The dynamic planning process in this step involves a comprehensive evaluation of multiple factors to ensure the safety and timeliness of the transfer route.

[0154] In the embodiment of this application, based on the remote medical support and treatment plan, the optimal transfer route is dynamically planned by comprehensively considering the legal constraints of international waters, the possibility of medical support along the way, and the urgency of the patient's condition. Through a multi-factor comprehensive evaluation model, a detailed scheduling action plan is generated to ensure that the patient can be quickly and safely transferred to a port or island with medical facilities for further treatment.

[0155] Suppose that after completing initial treatment, medical experts decide to transfer the patient to the nearest port with medical facilities for further treatment. The system first considers the legal constraints of international waters to ensure that the transfer route complies with relevant regulatory requirements. The system then evaluates the possibility of medical support along the way to confirm whether there are other ships or facilities that can provide assistance in an emergency. Considering the urgency of the patient's condition, the system prioritizes the fastest and safest transfer route. Finally, the system generates a detailed scheduling action plan that details the specific time and route arrangements for the transfer, including possible stops along the way and emergency contact methods. For example, the system selects the nearest international port as the destination and arranges a standby helicopter to provide air support when necessary to ensure that the patient can arrive at the destination in time for professional treatment.

[0156] Optionally, based on the remote medical support and treatment plan, the optimal transfer route to the nearest port or island with medical facilities is dynamically planned, taking into account legal constraints in international waters, the possibility of medical support along the way and the urgency of the patient's condition, to generate a detailed dispatch action plan, including:

[0157] Using the telemedicine support and treatment program, combined with the patient's real-time condition and required medical resources, the optimal transfer destination is preliminarily screened to obtain a list of candidate transfer destinations; based on the list of candidate transfer destinations, the legal constraints information of international waters, the possibility of medical support along the way and the urgency of the patient's condition are integrated, and a multi-factor comprehensive evaluation model is applied to quantitatively evaluate the accessibility and safety of each candidate destination to generate a destination evaluation report; based on the destination evaluation report, a dynamic path planning algorithm is used, combined with real-time traffic flow data analysis, weather forecast services and on-site safety risk assessment, to calculate the best travel route from the current location to each candidate destination to obtain an initial path solution set; using the initial path solution set, the direction and speed of the possible spread of the accident are simulated through the emergency impact range expansion technology, and the safety of the path is further predicted to obtain the optimal transfer route, and combined with the telemedicine support and treatment program, a detailed scheduling action plan is formed.

[0158] In this step, based on the telemedicine support and treatment plan, the optimal transfer route to the nearest port or island with medical facilities is dynamically planned, taking into account the legal constraints of international waters, the possibility of medical support along the way, and the urgency of the patient's condition, to generate a detailed dispatch action plan. Specifically, the list of candidate transfer destinations includes the results of preliminary screening of the optimal transfer destination in combination with the patient's real-time condition and the required medical resources; the destination evaluation report is generated by integrating the information on legal constraints in international waters, the possibility of medical support along the way, and the urgency of the patient's condition, and applying a multi-factor comprehensive evaluation model to quantitatively evaluate the accessibility and safety of each candidate destination; the initial path plan set is based on the destination evaluation report, using a dynamic path planning algorithm combined with real-time traffic flow data analysis, weather forecast services, and on-site safety risk assessment to calculate the best route from the current location to each candidate destination; the optimal transfer route is obtained by simulating the direction and speed of the possible spread of the accident through the emergency impact range expansion technology, and further predicting the safety of the path, and combining it with the telemedicine support and treatment plan to form a detailed dispatch action plan.

[0159] In an embodiment of the present application, firstly, the telemedicine support and treatment plan is used to perform preliminary screening of the optimal transfer destination in combination with the patient's real-time condition and required medical resources to obtain a list of candidate transfer destinations; secondly, based on the list of candidate transfer destinations, the legal constraints information of international waters, the possibility of medical support along the way, and the urgency of the patient's condition are integrated, and a multi-factor comprehensive evaluation model is applied to quantitatively evaluate the accessibility and safety of each candidate destination to generate a destination evaluation report; thirdly, based on the destination evaluation report, a dynamic path planning algorithm is used, combined with real-time traffic flow data analysis, weather forecast services, and on-site safety risk assessment, to calculate the optimal route from the current location to each candidate destination to obtain an initial path solution set; finally, using the initial path solution set, the direction and speed of the possible spread of the accident are simulated through the emergency impact range expansion technology, the safety of the path is further predicted and processed to obtain the optimal transfer route, and combined with the telemedicine support and treatment plan, a detailed scheduling action plan is formed.

[0160] Suppose a passenger on a cruise ship in a certain area of ​​the Mediterranean Sea suddenly suffers a serious heart attack. After receiving the distress signal, the system selects the most appropriate medical response unit and establishes a high-definition video connection, generating a personalized preliminary treatment plan. First, the system uses this preliminary treatment plan, combined with the patient's real-time condition (such as electrocardiogram, blood pressure, etc.) and the required medical resources (such as ICU beds, cardiac surgery equipment), to conduct a preliminary screening of the optimal transfer destination, and obtains a list of candidate transfer destinations including several major ports and islands nearby. Secondly, based on the list of candidate transfer destinations, the system integrates information on legal constraints in international waters (such as territorial boundaries and passage permits), the possibility of medical support along the way (such as the location and availability of ships and rescue helicopters along the way), and the urgency of the patient's condition, and applies a multi-factor comprehensive evaluation model to quantitatively evaluate the accessibility and safety of each candidate destination, generating a detailed destination evaluation report. report; secondly, based on the destination assessment report, the system uses a dynamic path planning algorithm, combined with real-time traffic flow data analysis (such as the busyness of the waterway), weather forecast services (such as weather conditions such as wind speed and wave height) and on-site safety risk assessment (such as offshore construction areas and potential dangerous objects), to calculate and process the best travel route from the current location to each candidate destination, and obtain a series of initial path solution sets; finally, using the initial path solution set, the system simulates the direction and speed of the possible spread of the accident through the emergency impact range expansion technology, further predicts the safety of the path, and finally determines an optimal transfer route, and combines remote medical support and treatment plans to form a detailed scheduling action plan to ensure that patients can quickly and safely reach the nearest and most suitable medical facilities; through the above steps, the system provides a scientific and reasonable transfer plan for this maritime emergency medical incident to ensure that patients can receive timely and efficient treatment.

[0161] In summary, the present invention covers the entire process from receiving an emergency medical assistance signal to generating a detailed dispatch action plan, aiming to provide a comprehensive, efficient and accurate marine medical emergency response system to meet the needs of rapid, safe and personalized medical rescue.

[0162] Figure 2 The present application provides a schematic diagram of a structure of a system for implementing real-time medical response and dispatching at sea based on adaptive satellite and ground network switching, such as Figure 2 As shown, the device comprises:

[0163] The receiving module 21 is used to receive an emergency medical help signal from a ship or platform at sea through an adaptively selected satellite communication network or a ground 5G network, receive an emergency medical help signal from a ship or platform at sea, process and obtain the precise geographic coordinates of the help location, environmental conditions and preliminary diagnosis information of the patient, and generate a comprehensive report on the emergency medical event;

[0164] The evaluation module 22 is used to evaluate the time and feasibility of different marine medical rescue resources arriving at the place of help based on the comprehensive report of the emergency medical incident, combined with the dynamic meteorological data of the sea area and the ocean current forecast, and apply the intelligent resource matching algorithm, analyze the influence of weather changes and sea conditions through the influencing factor sensitivity analysis technology, ensure the selected medical response unit to operate efficiently under various conditions, and obtain the most suitable medical response unit;

[0165] The analysis module 23 is used to establish a high-definition video connection between the help-seeking site and the land medical center using a two-way satellite link based on the most suitable medical response unit, and introduce a remote medical decision-making support system, adopt a disease progression prediction algorithm, analyze and process the historical case database and real-time physiological parameter monitoring data, provide accurate treatment suggestions and guidance, and obtain remote medical support and treatment plans;

[0166] The planning module 24 is used to dynamically plan the optimal transfer route to the nearest port or island with medical facilities based on the remote medical support and treatment plan, taking into account the legal constraints of international waters, the possibility of medical support along the way and the urgency of the patient's condition, and generate a detailed scheduling action plan.

[0167] Figure 2 The system for implementing real-time medical response and dispatching at sea based on adaptive satellite and ground network switching can be executed Figure 1 The implementation principle and technical effect of the method for implementing real-time response and scheduling of medical treatment at sea based on adaptive satellite and ground network switching described in the embodiment shown are not repeated here. The specific manner in which each module and unit performs operations in the system for implementing real-time response and scheduling of medical treatment at sea based on adaptive satellite and ground network switching in the above embodiment has been described in detail in the embodiment of the method, and will not be elaborated here.

[0168] In one possible design, Figure 2 The embodiment shown in the figure can be implemented as a computing device, such as a real-time marine medical response and dispatching system based on adaptive satellite and ground network switching. Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0169] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0170] The processing component 32 is used to: receive emergency medical help signals from offshore vessels or platforms through an adaptively selected satellite communication network or ground 5G network, receive emergency medical help signals from offshore vessels or platforms, process and obtain the precise geographic coordinates of the help location, environmental conditions and preliminary patient diagnosis information, and generate a comprehensive report on emergency medical events; based on the comprehensive report on emergency medical events, combined with dynamic meteorological data of the sea area and ocean current forecasts, apply an intelligent resource matching algorithm to evaluate the time and feasibility of different marine medical rescue resources arriving at the help location, analyze the impact of weather changes and sea conditions through influencing factor sensitivity analysis technology, and ensure that the selected medical response unit is in a variety of conditions. The system can operate efficiently under the optimal medical response unit to obtain the most suitable medical response unit; based on the most suitable medical response unit, a high-definition video connection is established between the scene of the call and the land medical center using a two-way satellite link, and a remote medical decision-making support system is introduced. The disease progression prediction algorithm is used to analyze and process the historical case library and real-time physiological parameter monitoring data to provide accurate treatment suggestions and guidance, and obtain remote medical support and treatment plans; based on the remote medical support and treatment plans, the optimal transfer route to the nearest port or island with medical facilities is dynamically planned, and a detailed scheduling action plan is generated taking into account the legal constraints of international waters, the possibility of medical support along the way, and the urgency of the patient's condition.

[0171] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component may also be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0172] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0173] Of course, the computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0174] The input / output interface provides an interface between the processing component and the peripheral interface module, which may be an output device, an input device, etc.

[0175] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0176] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0177] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 The illustrated embodiment provides a method for implementing real-time medical response and scheduling at sea based on adaptive satellite and ground network switching.

[0178] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0179] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0180] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0181] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for implementing real-time response and scheduling of medical services at sea based on adaptive satellite and ground network switching, characterized in that: include: Through adaptively selected satellite communication networks or ground 5G networks, emergency medical assistance signals from offshore vessels or platforms are processed and obtained, including precise geographic coordinates of the assistance location, environmental conditions, and preliminary patient diagnosis information, to generate a comprehensive report on emergency medical events; Based on the comprehensive report of the emergency medical incident, combined with the dynamic meteorological data of the sea area and the ocean current forecast, the intelligent resource matching algorithm is applied to evaluate the time and feasibility of different marine medical rescue resources arriving at the place of help, and the influence of weather changes and sea conditions is analyzed through the sensitivity analysis technology of influencing factors to ensure that the selected medical response unit operates efficiently under various conditions and obtain the most suitable medical response unit; Based on the most suitable medical response unit, a high-definition video connection is established between the scene of the call for help and the land medical center using a two-way satellite link, and a remote medical decision-making support system is introduced. The disease progression prediction algorithm is used to analyze and process the historical case database and real-time physiological parameter monitoring data to provide accurate treatment suggestions and guidance, and obtain remote medical support and treatment plans; and when the two-way satellite link is unavailable, it automatically switches to the ground 5G network to ensure that the high-definition video connection is not interrupted; Based on the telemedicine support and treatment plan, the optimal transfer route to the nearest port or island with medical facilities is dynamically planned, taking into account the legal constraints of international waters, the possibility of medical support along the way and the urgency of the patient's condition, and generating a detailed scheduling action plan.

2. The method according to claim 1, characterized in that According to the comprehensive report of the emergency medical incident, combined with the dynamic meteorological data of the sea area and the ocean current forecast, the intelligent resource matching algorithm is applied to evaluate the time and feasibility of different marine medical rescue resources to arrive at the place of help, and the influence of weather changes and sea conditions is analyzed through the sensitivity analysis technology of influencing factors to ensure that the selected medical response unit operates efficiently under various conditions and obtain the most suitable medical response unit, including: Using the comprehensive emergency medical incident report, conduct a preliminary assessment of the location information of different maritime medical rescue resources and their accessibility and transportation safety to obtain a preliminary response effectiveness evaluation; Based on the preliminary response effectiveness evaluation, combined with the dynamic meteorological data of the sea area and the ocean current forecast, the intelligent resource matching algorithm is applied to quantitatively evaluate the time and feasibility of each medical rescue resource arriving at the place of help, and generate a medical rescue resource evaluation result; Based on the medical rescue resource assessment results, the influencing factor sensitivity analysis technology is used to deeply analyze the weather changes and sea conditions to obtain an influencing factor analysis report; The influencing factor analysis report is used to conduct a final review of the operating efficiency of each medical rescue resource under different conditions to ensure that the selected medical response unit can operate efficiently under various conditions and obtain the most suitable medical response unit.

3. The method according to claim 2, characterized in that Based on the medical rescue resource assessment results, the influencing factor sensitivity analysis technology is used to deeply analyze weather changes and sea conditions to obtain an influencing factor analysis report, including: Using the medical rescue resource assessment results, data on weather changes and sea conditions are collected and processed to generate an original influencing factor data set; Based on the original influencing factor data set, a multi-factor comprehensive evaluation model is applied to quantitatively analyze the importance and mutual relationship of each factor to generate a factor importance score table; Based on the factor importance score table, combined with the successful experiences and lessons learned from historical rescue cases, the potential impact of each influencing factor is deeply analyzed and processed to obtain the influencing factor analysis results; The analysis results of the influencing factors are integrated to form a comprehensive influencing factor analysis report.

4. The method according to claim 2, characterized in that: The influencing factor analysis report is used to conduct a final review of the operating efficiency of each medical rescue resource under different conditions to ensure that the selected medical response unit can operate efficiently under various conditions and obtain the most suitable medical response unit, including: Using the influencing factor analysis report, the operational efficiency of each medical rescue resource under different weather conditions and sea conditions is quantitatively evaluated to obtain an operational efficiency score; Based on the operational efficiency score and combined with the successful experiences and lessons learned in the historical rescue case library, a comprehensive evaluation is conducted on the adaptability and reliability of each medical rescue resource to generate a medical rescue resource adaptability report; Based on the medical rescue resource adaptability report, a multi-dimensional performance optimization algorithm is applied to conduct a final review of the overall performance of each medical rescue resource to determine the optimal medical response unit; The optimal medical response unit is confirmed to ensure that it can operate efficiently under various conditions, and ultimately the most suitable medical response unit is generated.

5. The method according to claim 1, characterized in that Based on the most suitable medical response unit, a high-definition video connection is established between the help-seeking site and the land medical center using a two-way satellite link, and a remote medical decision-making support system is introduced. The disease progression prediction algorithm is used to analyze and process the historical case database and real-time physiological parameter monitoring data, provide accurate treatment suggestions and guidance, and obtain remote medical support and treatment plans, including: Utilizing the optimal medical response unit, combined with high-precision positioning technology and two-way satellite link technology, a high-definition video connection between the scene of the call and the land-based medical center is configured and optimized to ensure stable, low-latency communication quality and support high-definition video connection; Based on the HD video connection support, a remote medical decision-making support system is introduced, integrating two-way video consultation and disease tracking functions, realizing real-time interaction and guidance between the help-seeking site and land medical experts, and generating a comprehensive remote medical monitoring platform; Based on the remote medical monitoring platform, the disease progression prediction algorithm is applied to comprehensively analyze and process similar cases in the historical case database and the real-time physiological parameter monitoring data at the scene of help-seeking, and provide accurate treatment suggestions and guidance in combination with the patient's personalized factors, and generate a personalized preliminary treatment plan; The personalized preliminary treatment plan is used in combination with the real-time feedback provided by the telemedicine monitoring platform and the professional opinions of the expert system, and comprehensive evaluation and adjustment are performed through an intelligent optimization algorithm to obtain telemedicine support and treatment plans.

6. The method according to claim 5, characterized in that The personalized preliminary treatment plan is used in combination with the real-time feedback provided by the telemedicine monitoring platform and the professional opinions of the expert system, and a comprehensive evaluation and adjustment is performed through an intelligent optimization algorithm to obtain telemedicine support and treatment plans, including: Using the personalized preliminary treatment plan, the patient's current condition and possible development trend are estimated and processed, and a condition estimation report is generated; According to the disease prediction report, combined with the high-definition video connection support and real-time physiological parameter monitoring data provided by the remote medical monitoring platform, the actual situation of the patient is continuously tracked and dynamically evaluated to obtain a real-time disease tracking record; Based on the real-time disease tracking records, the professional opinions of the expert system are introduced, and the intelligent optimization algorithm is used to comprehensively evaluate and adjust the preliminary treatment plan, considering the effects and potential risks of different treatment measures, and generating optimized treatment recommendations; Utilizing the optimized treatment recommendations and combining them with the comprehensive support functions of the telemedicine monitoring platform, a telemedicine support and treatment plan is ultimately determined.

7. The method according to claim 1, characterized in that Based on the telemedicine support and treatment plan, the optimal transfer route to the nearest port or island with medical facilities is dynamically planned, taking into account the legal constraints of international waters, the possibility of medical support along the way and the urgency of the patient's condition, and generating a detailed dispatch action plan, including: Using the remote medical support and treatment plan, combined with the patient's real-time condition and required medical resources, the optimal transfer destination is preliminarily screened to obtain a list of candidate transfer destinations; Based on the list of candidate transshipment destinations, the legal constraints in international waters, the possibility of medical support along the way, and the urgency of the patient's condition are integrated, and a multi-factor comprehensive evaluation model is applied to quantitatively evaluate the accessibility and safety of each candidate destination to generate a destination evaluation report; Based on the destination assessment report, the optimal route from the current location to each candidate destination is calculated and processed using a dynamic path planning algorithm, combined with real-time traffic flow data analysis, weather forecast services, and on-site safety risk assessment to obtain an initial path solution set; Utilizing the initial path plan set, the possible direction and speed of the accident spread are simulated through the emergency impact range expansion technology, and the safety of the path is further predicted and processed to obtain the optimal transfer route. Combined with the remote medical support and treatment plan, a detailed scheduling action plan is formed.

8. A system for implementing real-time medical response and dispatching at sea based on adaptive satellite and ground network switching, characterized in that: include: A receiving module is used to receive emergency medical assistance signals from offshore vessels or platforms through an adaptively selected satellite communication network or a ground 5G network, receive emergency medical assistance signals from offshore vessels or platforms, process and obtain precise geographic coordinates of the assistance location, environmental conditions and preliminary patient diagnosis information, and generate a comprehensive report on emergency medical events; An evaluation module is used to evaluate the time and feasibility of different marine medical rescue resources arriving at the place of help based on the comprehensive report of the emergency medical incident, combined with dynamic meteorological data of the sea area and ocean current forecasts, and apply an intelligent resource matching algorithm, analyze the influence of weather changes and sea conditions through the sensitivity analysis technology of influencing factors, ensure that the selected medical response unit operates efficiently under various conditions, and obtain the most suitable medical response unit; An analysis module is used to establish a high-definition video connection between the scene of the call and the land medical center based on the most suitable medical response unit using a two-way satellite link, introduce a remote medical decision-making support system, use a disease progression prediction algorithm, analyze and process the historical case database and real-time physiological parameter monitoring data, provide accurate treatment suggestions and guidance, and obtain remote medical support and treatment plans; and automatically switch to the ground 5G network when the two-way satellite link is unavailable to ensure that the high-definition video connection is not interrupted; The planning module is used to dynamically plan the optimal transfer route to the nearest port or island with medical facilities based on the remote medical support and treatment plan, taking into account the legal constraints of international waters, the possibility of medical support along the way and the urgency of the patient's condition, and generate a detailed scheduling action plan.

9. A computing device, characterized in that It comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for realizing real-time response and scheduling of medical treatment at sea based on adaptive satellite and ground network switching as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a computer, a method for realizing real-time response and scheduling of medical treatment at sea based on adaptive satellite and ground network switching as described in any one of claims 1 to 7 is implemented.

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