Intelligent medical management system based on artificial intelligence

Abstract

The invention discloses an intelligent medical management system based on artificial intelligence, and relates to the field of data processing, and the system comprises a sensing module which is used for sensing the position information of medical personnel in a hospital and an emergency transportation sickbed in real time; the labeling module is used for labeling available operating rooms on the in-hospital path three-dimensional topology in real time; by sensing the positions of medical workers and emergency transport sickbeds in real time, marking available operating rooms on a three-dimensional topology, intelligently deciding medical worker configuration and sickbed moving paths, visualizing the paths and directions through a public area display, and playing early warning audio to prompt evacuation, the first-aid efficiency is effectively improved, precious time is won for patients, and the medical workers and the emergency transport sickbeds are protected. And the first-aid channel is ensured to be smooth, so that the in-hospital multi-source resource scheduling arrangement of the medical first-aid scene is more scientific, reasonable and orderly.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to an intelligent medical management system based on artificial intelligence. Background Art

[0002] Medical affairs generally refer to activities related to medical affairs in hospitals, covering clinical work such as diagnosis, treatment, and nursing.

[0003] The invention patent application with application number 202211099561.2 discloses a smart medical management platform, including a network application with a B / S structure, which can enable different personnel to access and operate a common database from different locations in different access methods; using the Microsoft DoNet FrameWork framework, this system is an application system that combines real-time online processing (0LTP) with real-time online analytical processing (0LAP): based on the S0A structural system, the different functional units of the application (called services) are connected through well-defined interfaces and contracts between these services; using the MVC architecture to represent a software architecture pattern, the software system is divided into three basic parts: model (M ode1), view (View) and controller (Controller); XML-based interface standards; and use middleware technology to support system software for application software development and operation; the platform aims to build a harmonious doctor-patient relationship and firmly establish the service concept of "patient health as the center", which will effectively strengthen the construction of digital hospitals, promote the continuous improvement of medical quality, improve the efficiency of medical management, ensure medical safety, improve the management of clinical medical and technical specialty capabilities and expert capabilities, meet the actual needs of hospital medical management, and form a systematic, information-based, and precise medical quality and safety management information system. This application aims to solve the problem of "hospital medical management information being scattered and overlapping, and no unified management system has been formed."

[0004] However, in ambulance rescue scenarios, after the ambulance arrives at the hospital, existing technologies do not have a special multi-source coordination technology solution for such scenarios, so that the operating room, medical staff, and patient flow paths mostly rely on manual arrangements, and the timeliness of the reception and treatment process has a lot of room for optimization and improvement.

[0005] To this end, an intelligent medical management system based on artificial intelligence is proposed. Summary of the Invention

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides an intelligent medical management system based on artificial intelligence, which can effectively solve the problems of the prior art.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] The present invention discloses an intelligent medical management system based on artificial intelligence, comprising:

[0009] The perception module is used to perceive the location information of medical staff and emergency transport beds in the hospital in real time; the labeling module is used to label the available operating rooms on the three-dimensional topology of the hospital path in real time; the decision module is used to receive the location information of medical staff and emergency transport beds perceived by the perception module and the available operating rooms labeled by the labeling module, and use the location information of medical staff, emergency transport beds and available operating rooms to decide on the configuration of medical staff and the path for the emergency transport beds to move to the available operating rooms; the visualization module is used to interact with all public area displays in the hospital, obtain the path for the emergency transport beds to move to the available operating rooms output by the decision module, display the path for the emergency transport beds to move to the available operating rooms on all public area displays, and indicate the path direction with an arrow icon on the displayed path for the emergency transport beds to move to the available operating rooms; the global warning module is used to play warning audio;

[0010] Among them, the early warning audio stores voice audio that reminds people in the hospital to evacuate and keep the roads clear.

[0011] Furthermore, the emergency transport bed in the sensing module is a bed used to transport patients who need immediate medical treatment or are transported by ambulance due to sudden illness;

[0012] The sensing module is integrated with a number of position sensors. Each of the medical staff and emergency transport beds in the hospital is equipped with at least one sensing module. When sensing position information, the sensing module uses any position in the hospital as a reference origin coordinate and outputs its own position information.

[0013] A construction unit is provided inside the perception module, and the construction unit is used to upload the location information of each path segment within the hospital and use the location information of the path within the hospital to construct a three-dimensional topology of the path within the hospital;

[0014] Among them, all location information perceived by the perception module is represented on the three-dimensional topology of the hospital path. All perception modules configured for medical staff are in standby state, and all perception modules configured for emergency transport beds are in real-time operation state. When any perception module configured for emergency transport beds perceives that its own position has changed, it triggers all perception modules configured for medical staff to switch to real-time operation state.

[0015] Furthermore, the operating rooms are all marked on the three-dimensional topology of the hospital path, and the system end user manually switches the text labels of the operating rooms to available or occupied in real time through the marking module. The lower level of the marking module is provided with a monitoring unit, which is used to monitor the operating status of the perception module configured for medical staff in real time. When the perception module is detected to be in real-time operation, the monitoring unit synchronously performs the matching operation of the emergency transport bed and the operating room;

[0016] The matching logic between emergency transport beds and operating rooms is expressed as follows:

[0017] Based on the perception module, the location information of the emergency transport bed is obtained in real time, the operating room closest to the location information of the emergency transport bed based on the three-dimensional topology of the intra-hospital path is identified, and the identified operating room is matched with the emergency transport bed.

[0018] Furthermore, the decision module runs the received available operating room marked by the marking module, that is, the operating room identified by the monitoring unit and then matched with the emergency transport bed;

[0019] The path for the emergency transport bed to move to the available operating room determined by the decision module is: the intra-hospital path used to determine the matching result between the operating room and the emergency transport bed, from the matching result between the emergency transport bed and the operating room obtained by the monitoring unit;

[0020] Among them, an interactive unit is set inside the decision module, and the interactive unit is used to feedback the path of the emergency transport bed decided by the decision module during the operation phase to the available operating room to the operating room to the marking module. The marking module marks the operating room as occupied on the three-dimensional topology of the hospital path.

[0021] Furthermore, the decision logic for medical staff allocation in the decision module complies with:

[0022] Identify the path of the emergency transport bed to the available operating room on the three-dimensional topology of the hospital path, and simultaneously set the medical staff capture range. Use the medical staff capture range as the radius and all points on the path of the emergency transport bed to the available operating room as the origin to determine the medical staff capture area. Combined with the in-hospital medical staff location information perceived by the perception module, all medical staff within the medical staff capture area are obtained.

[0023] The demand for medical staff is set, the medical staff allocation tendency values ​​obtained in the medical staff capture area are analyzed, and the medical staff are arranged in descending order based on the tendency values. The medical staff corresponding to the set medical staff demand are selected at the front position in the descending medical staff queue as the medical staff allocation result.

[0024] Furthermore, a reset unit is provided at the lower level of the decision module, and the reset unit is used to refresh the decision logic of the medical staff configuration in the decision module;

[0025] Among them, when the decision module refreshes the operation through the reset unit, the set medical staff capture range is increased to 3 / 2 of the original medical staff capture range, and so on, until the number of medical staff included in the descending medical staff queue is not less than the medical staff demand.

[0026] Furthermore, during the operation phase of the decision module, it interacts with each elevator in the hospital to control the operation of each elevator so that on all sections of the path where the emergency transport bed is moved to the available operating room, there is at least one elevator corresponding to each section that is on the corresponding indicated floor on the path where the emergency transport bed is moved to the available operating room.

[0027] Furthermore, the medical staff configuration propensity value analysis logic is expressed as:

[0028] ;

[0029] Where: Assign propensity scores to healthcare workers; The medical staff demand level in the area corresponding to the medical staff's location; The shortest straight-line distance from the location of the medical staff to the path of the emergency transport bed to the available operating room; For medical staff The path distance from the medical staff's location to the end point of the emergency transport bed's path to the available operating room after the path reaches the path for the emergency transport bed to move to the available operating room; Online hours for healthcare workers;

[0030] Among them, medical staff online time That is, the current cumulative continuous working hours of medical staff, The intensive care unit is the first level, the inpatient convalescent unit is the second level, the inspection and medication distribution unit is the third level, and other hospital areas are the fourth level. The larger it is, the more suitable the medical staff is to be selected as the medical staff included in the medical staff configuration results.

[0031] Furthermore, during the operation phase of the visualization module, all selected medical staff, i.e., the medical staff configuration results, are synchronously displayed on the path of the emergency transport bed moving to the available operating room displayed on the public area display. A speaker is also integrated into the perception module configured for the medical staff, and the speaker stores prompt audio. During the operation phase of the visualization module, the speaker integrated into the perception module of the selected medical staff is synchronously triggered to play the prompt audio in a loop.

[0032] Among them, the medical staff corresponding to the sensing module where all the speakers playing the prompt audio are located read the path and direction of the emergency transport bed moving to the available operating room based on the display in the public area of ​​the hospital, and move along the path and direction. If they encounter an elevator, they confirm whether the elevator is on the current floor;

[0033] If the elevator is on the current floor, it will wait; if the elevator is not on the current floor, it will continue to move;

[0034] If you encounter an elevator again, perform the above operations again.

[0035] Furthermore, the perception module is interactively connected with a construction unit via a wireless network, the perception module is interactively connected with the labeling module via a wireless network, the labeling module is interactively connected with a monitoring unit at a lower level via a wireless network, the monitoring unit is interactively connected with the perception module via a wireless network, the labeling module is interactively connected with a decision module via a wireless network, the decision module is interactively connected with an interaction unit via a wireless network, the interaction unit is interactively connected with the labeling module via a wireless network, the decision module is interactively connected with a reset unit at a lower level via a wireless network, and the decision module is interactively connected with a visualization module and a global warning module via a wireless network.

[0036] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0037] The present invention provides an artificial intelligence-based smart medical management system. During operation, the system senses the location of medical staff and emergency transport beds in real time, marks available operating rooms on a three-dimensional topology, intelligently determines the allocation of medical staff and the movement path of beds, and visualizes the path and direction on public area displays. It also plays an audio warning to prompt evacuation, effectively improving emergency treatment efficiency, buying valuable time for patients, ensuring unobstructed emergency channels, and making the scheduling of multi-source resources within the hospital for medical emergency scenarios more scientific, reasonable, and orderly.

[0038] During operation, the system can automatically match the nearest operating room, dynamically adjust the capture range of medical staff, select medical staff according to the propensity value, control the elevator to stop at the designated floor, quickly build the path topology within the hospital, and synchronously display medical staff on the path. It also plays prompt sounds through the speaker in a loop to guide the movement, realizing the intelligent allocation of emergency medical resources and path optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0040] Figure 1 This is a structural diagram of an intelligent medical management system based on artificial intelligence. DETAILED DESCRIPTION

[0041] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0042] The present invention will be further described below with reference to the embodiments.

[0043] Example:

[0044] This embodiment is an intelligent medical management system based on artificial intelligence, such as Figure 1 Shown, including:

[0045] The sensing module is used to sense the real-time location of medical staff and emergency transport beds in the hospital;

[0046] The emergency transport bed in the sensing module is a bed used to transport patients who need immediate medical treatment or are transported by ambulance due to sudden illness;

[0047] The sensing module is integrated with several position sensors. Each medical staff and emergency transport bed in the hospital is equipped with at least one sensing module. When the sensing module senses the position information, it uses any position in the hospital as the reference origin coordinate and outputs its own position information.

[0048] A construction unit is set up inside the perception module, which is used to upload the location information of each path segment within the hospital and use the location information of the path within the hospital to construct the three-dimensional topology of the path within the hospital;

[0049] Among them, all the location information perceived by the perception modules is represented on the three-dimensional topology of the hospital path. All the perception modules configured for medical staff are in standby mode, and all the perception modules configured for emergency transport beds are in real-time operation mode. When any perception module configured for emergency transport beds senses a change in its own position, it triggers all the perception modules configured for medical staff to switch to real-time operation mode.

[0050] Through the above settings, the real-time location of medical staff in the hospital is perceived, which provides support for the operation of subsequent modules of the system in this embodiment and ensures the correct selection and decision of appropriate medical staff;

[0051] A labeling module is used to label available operating rooms in real time on the 3D topology of the hospital pathways;

[0052] Operating rooms are all marked on the three-dimensional topology of the hospital's paths, and the system end user manually switches the text labels of the operating rooms in real time through the annotation module. The annotation module is equipped with a monitoring unit at the lower level. The monitoring unit is used to monitor the operating status of the perception module configured for medical staff in real time. When the perception module is detected to be in real-time operation, the emergency transport bed is matched with the operating room synchronously.

[0053] The matching logic between emergency transport beds and operating rooms is expressed as follows:

[0054] Based on the perception module, the location information of the emergency transport bed is obtained in real time, the operating room closest to the location information of the emergency transport bed based on the three-dimensional topology of the intra-hospital path is identified, and the identified operating room is matched with the emergency transport bed;

[0055] The decision module is used to receive the location information of medical staff and emergency transport beds perceived by the perception module and the available operating rooms annotated by the annotation module, and use the location information of medical staff and emergency transport beds and the available operating rooms to decide on the allocation of medical staff and the path for the emergency transport beds to move to the available operating rooms;

[0056] The decision module runs the received available operating room marked by the marking module, that is, the operating room identified by the monitoring unit and then matched with the emergency transport bed;

[0057] The path of the emergency transport bed to the available operating room determined by the decision module is: the intra-hospital path used to determine the matching result between the operating room and the emergency transport bed from the matching result between the emergency transport bed and the operating room obtained by the monitoring unit;

[0058] The decision module is internally provided with an interaction unit, which is used to feed back the path of the emergency transport bed to the available operating room determined by the decision module during the operation phase to the marking module. The marking module then marks the operating room as occupied on the three-dimensional topology of the hospital path.

[0059] The decision logic for medical staff allocation in the decision module follows:

[0060] Identify the path of the emergency transport bed to the available operating room on the three-dimensional topology of the hospital path, and simultaneously set the medical staff capture range. Use the medical staff capture range as the radius and all points on the path of the emergency transport bed to the available operating room as the origin to determine the medical staff capture area. Combined with the in-hospital medical staff location information perceived by the perception module, all medical staff within the medical staff capture area are obtained.

[0061] Set the demand for medical personnel, analyze the medical personnel allocation tendency values ​​obtained in the medical personnel capture area, sort the medical personnel in descending order based on the tendency value, and select the medical personnel corresponding to the set medical personnel demand at the front position in the descending medical personnel queue as the medical personnel allocation result;

[0062] A reset unit is provided at the lower level of the decision module, which is used to refresh the decision logic of the medical staff configuration in the decision module;

[0063] Among them, when the decision module refreshes the operation through the reset unit, the set medical staff capture range is increased to 3 / 2 of the original medical staff capture range, and so on, until the number of medical staff included in the descending order medical staff queue is not less than the medical staff demand;

[0064] During the decision-making module's operation phase, it interacts with the hospital's elevators and controls their operation so that on all sections of the path where the emergency bed is transported to an available operating room, there is at least one elevator on each section that is located on the floor indicated by the emergency bed's route.

[0065] The logic of the propensity value analysis of medical staff configuration is expressed as follows:

[0066] ;

[0067] Where: Assign propensity scores to healthcare workers; The location of the medical staff corresponds to the level of medical staff demand in the area; The shortest straight-line distance from the location of the medical staff to the path of the emergency transport bed to the available operating room; For medical staff The path distance from the medical staff's location to the end point of the emergency transport bed's path to the available operating room after the path reaches the path for the emergency transport bed to move to the available operating room; Online hours for healthcare workers;

[0068] Among them, medical staff online time That is, the current cumulative continuous working hours of medical staff, The intensive care unit is the first level, the inpatient convalescent unit is the second level, the inspection and medication distribution unit is the third level, and other hospital areas are the fourth level. The larger it is, the more suitable the medical staff is to be selected as the medical staff included in the medical staff configuration results;

[0069] The above logical formula calculates and quantifies the medical staff configuration tendency, thereby assisting medical staff in selecting and moving the emergency transport bed to the available operating room, ensuring that patients can complete all preoperative configurations more quickly.

[0070] A visualization module is used to interact with all public area displays in the hospital, obtain the path of the emergency transport bed moving to the available operating room output by the decision module, display the path of the emergency transport bed moving to the available operating room on all public area displays, and indicate the path direction with an arrow icon on the displayed path of the emergency transport bed moving to the available operating room;

[0071] During the operation phase of the visualization module, all selected medical staff are synchronously displayed on the path of the emergency transport bed moving to the available operating room on the display in the public area, that is, the medical staff configuration result. The perception module configured in the medical staff is also integrated with a speaker, and the speaker stores prompt audio. During the operation phase of the visualization module, the speaker integrated in the perception module of the selected medical staff is synchronously triggered to play the prompt audio in a loop;

[0072] Among them, the medical staff corresponding to the sensing module where all the speakers playing the prompt audio are located read the path and direction of the emergency transport bed moving to the available operating room based on the display in the public area of ​​the hospital, and move along the path and direction. If they encounter an elevator, they confirm whether the elevator is on the current floor;

[0073] If the elevator is at the current floor, it will wait; if the elevator is not at the current floor, it will continue to move;

[0074] If you encounter an elevator again, perform the above operations again;

[0075] Global warning module, used to play warning audio;

[0076] The perception module is interactively connected to a construction unit via a wireless network. The perception module is interactively connected to the labeling module via a wireless network. The labeling module is interactively connected to a monitoring unit at a lower level via a wireless network. The monitoring unit is interactively connected to the perception module via a wireless network. The labeling module is interactively connected to a decision module via a wireless network. The decision module is interactively connected to an interaction unit via a wireless network. The interaction unit is interactively connected to the labeling module via a wireless network. The decision module is interactively connected to a reset unit at a lower level via a wireless network. The decision module is interactively connected to a visualization module and a global warning module via a wireless network.

[0077] Among them, the early warning audio stores voice audio that reminds people in the hospital to evacuate and keep the roads clear.

[0078] In this embodiment, the perception module runs in real time to perceive the location information of medical staff and emergency transport beds in the hospital, the construction unit synchronously uploads the location information of each section of the path in the hospital, and uses the location information of the path in the hospital to construct the three-dimensional topology of the path in the hospital. The labeling module runs in the post-hospital to label the available operating rooms in real time on the three-dimensional topology of the path in the hospital. The monitoring unit monitors the running status of the perception module configured for the medical staff in real time. When it is detected that the perception module is in real-time running status, the matching operation of the emergency transport bed and the operating room is synchronously executed. The decision module further runs to receive the medical staff and emergency transport bed location information perceived by the perception module and the available operating rooms marked by the labeling module, and uses the medical staff, emergency transport bed location information and available operating rooms to decide on the configuration of medical staff, emergency transport bed and operating room. The path of the emergency transport bed to the available operating room, the interactive unit synchronously points the path of the emergency transport bed to the available operating room decided by the decision module during the operation phase to the operating room and feeds it back to the marking module. The marking module switches the marking of the operating room on the three-dimensional topology of the hospital path to occupied. The reset unit refreshes the decision logic of the medical staff configuration in the decision module in real time. Then the visualization module runs and interacts with all public area displays in the hospital to obtain the path of the emergency transport bed to the available operating room output by the decision module. The path of the emergency transport bed to the available operating room is displayed on all public area displays, and the path direction is indicated by an arrow icon on the displayed path of the emergency transport bed to the available operating room. Finally, the warning audio is played through the global warning module.

[0079] Through the operation of the system in the above embodiment, a designated optimal transfer path is provided for patients arriving by ambulance. During the patient transfer process, the medical staff configuration is adaptively optimized so that the medical staff can go to the preset operating room in coordination. Before the patient arrives at the operating room, the medical staff arrives at the same time, thereby improving the timeliness of the patient's reception and treatment process and opening up a more reliable "life channel" for the patient.

[0080] The following is an example application example of the system in the above embodiment:

[0081] 1. Emergency First Aid Scenario Background

[0082] At 10:00 AM on June 23, 2025, the emergency center at the Central Hospital received a call about a 55-year-old male patient who had suffered an acute myocardial infarction on his way to work. An ambulance was being transported to the hospital at maximum speed, with an estimated arrival time of 5 minutes. The patient was in critical condition and required immediate cardiac intervention.

[0083] 2. Collaborative Workflow of System Modules

[0084] (1) Real-time positioning of the perception module

[0085] When the ambulance enters the hospital campus, the sensing module installed on the emergency transport bed is immediately triggered. With the hospital emergency door as the reference origin coordinate (0,0,0), the bed location information is uploaded in real time. For example, (100,20,0) indicates that the bed is located on the ground floor, 100 meters away from the emergency door and 20 meters horizontally.

[0086] At the same time, the construction unit of the perception module has uploaded the location information of each section of the path in the hospital in advance and constructed a three-dimensional topological map of the path in the hospital. This topological map clearly shows the location and connection relationship of corridors, stairs, elevators and other passages on each floor of the hospital.

[0087] The sensing modules installed on medical staff in various departments of the hospital, which were originally in standby mode, all switched to real-time operation mode after receiving the emergency transport bed position change signal, and provided real-time feedback on the medical staff's location information. For example, the current location of Dr. Zhang in the Department of Cardiology is (300, 50, 3), which means that he is on the third floor, 300 meters away from the origin and 50 meters horizontally.

[0088] (2) The marking module marks the available operating rooms

[0089] System users (such as hospital dispatch center staff) use the annotation module to view the current usage status of each operating room on the 3D topology map of the hospital's internal pathways. At this point, Cardiovascular Interventional Operating Room 302 is displayed as "Available," while other operating rooms, such as Room 301, are currently performing other surgeries, and Room 303 is undergoing disinfection.

[0090] The monitoring unit of the labeling module detects in real time that the perception module is in real-time operation and immediately starts matching the emergency transport bed with the operating room.

[0091] (3) Decision-making module for resource allocation and path planning

[0092] Operating room matching and path planning:

[0093] Based on the real-time location information of the emergency transport bed obtained by the sensing module, the monitoring unit calculated the closest available operating room to the bed on a three-dimensional topological map of the hospital's path. The distance between the two operating rooms on the three-dimensional topological map is: from the emergency entrance, through the first-floor corridor to the elevator lobby, take the elevator to the third floor, and then through the third-floor corridor to Room 302, for a total distance of approximately 150 meters (three-dimensional distance).

[0094] The decision module receives the matching results and determines the specific path for the emergency transport bed to move to Room 302: emergency door → first floor corridor (100 meters) → elevator hall → 3rd floor elevator → 3rd floor corridor (50 meters) → Room 302.

[0095] The interactive unit of the decision module feeds the path information back to the labeling module, which immediately switches the label of Room 302 on the three-dimensional topological map of the hospital path to "occupied" to avoid mistakenly selecting the operating room in other emergency situations.

[0096] Medical staff configuration:

[0097] The decision-making module identifies the path of the emergency transport bed moving to Room 302 on the three-dimensional topological map of the hospital path, takes all points on the path as the origin, sets the initial medical staff capture range to a radius of 50 meters, and determines the medical staff capture area.

[0098] Combined with the location information of medical staff fed back by the perception module, it was found that there were 5 medical staff in the capture area, namely Dr. Zhang and Nurse Li from the Department of Cardiology, Dr. Wang and Nurse Zhao from the Emergency Department, and Dr. Chen from the Department of Anesthesiology.

[0099] Assume that this emergency requires three medical personnel (one doctor and two nurses). The decision module analyzes the configuration preference values ​​of these five medical personnel:

[0100] Dr. Zhang: According to the formula, the propensity score is 0.25.

[0101] Nurse Li: According to the formula, the propensity score is 0.15.

[0102] Dr. Wang: According to the formula, the propensity value is 0.5.

[0103] Nurse Zhao: According to the formula, the propensity score is 0.18.

[0104] Dr. Chen: The propensity score calculated according to the formula is 0.375.

[0105] The propensity score ranking in descending order is: Dr. Wang (0.5) > Dr. Chen (0.375) > Dr. Zhang (0.25) > Nurse Zhao (0.18) > Nurse Li (0.15). The top three, Dr. Wang, Dr. Chen, and Nurse Zhang, are selected as the final medical staffing results.

[0106] Elevator Control:

[0107] The decision-making module interacts with the hospital's elevators to control the path of the emergency bed. If the path involves an elevator from the first to the third floor, the system will immediately direct that elevator to the first-floor elevator lobby to wait, ensuring it is at the designated floor when the bed arrives.

[0108] (IV) Visualization module displays the path and guides medical staff

[0109] The visualization module interacts with displays in all public areas of the hospital, showing the movement path of the emergency transport bed from the emergency gate to Room 302 on the display, and indicating the direction with arrow icons on the path, such as "Emergency gate→→First floor corridor→→Elevator hall→→3rd floor elevator→→3rd floor corridor→→Room 302".

[0110] At the same time, the selected medical staff configuration results (Dr. Wang, Dr. Chen, Nurse Zhao) and their current locations are displayed synchronously on the monitor, making it easier for other personnel to understand the movements of the emergency team.

[0111] The speakers integrated into the sensor modules installed on the three medical staff members were triggered, playing a looping audio prompt: "Emergency emergency mission, please proceed to the designated route and rendezvous immediately." Upon hearing the prompt, the medical staff read the route and directions on a display in a public area within the hospital and began following the route. When they reached the elevator lobby, they confirmed that the elevator was on the current floor (the 1st floor). Since the decision-making module had already arranged for the elevator to arrive early, the medical staff were able to take the elevator directly to the 3rd floor and then follow the directions to Room 302.

[0112] (V) Global early warning module ensures smooth passage

[0113] The global warning module begins playing an audio warning: "Attention, the emergency transport bed is en route to Operating Room 302. Please evacuate and keep the path clear." This warning plays in a loop throughout the hospital's public areas (corridors, lobbies, elevator halls, etc.), reminding staff to promptly yield to the emergency transport bed and ensure a clear path.

[0114] 3. Application Example Results

[0115] The entire process, from the ambulance arriving at the hospital to the patient entering the 302 operating room, took only 3 minutes, 2 minutes shorter than the traditional process.

[0116] Dr. Wang, Dr. Chen, and Nurse Zhao in the medical staff configuration results arrived at the operating room within 1 minute and prepared for the operation.

[0117] During the movement of the emergency transport bed, the road remained unobstructed and there was no congestion due to the prompts of the global warning module and the path guidance of the visualization module.

[0118] The patient entered the operating room in time to undergo cardiac interventional surgery. The operation went smoothly and he was ultimately out of danger.

[0119] In summary, in the above embodiments, during operation, the system perceives the positions of medical staff and emergency transport beds in real time, marks available operating rooms on the three-dimensional topology, intelligently decides on the configuration of medical staff and the movement path of the bed, and visualizes the path and direction through the public area display. At the same time, it plays an early warning audio prompt to evacuate, effectively improving the efficiency of emergency treatment, buying precious time for patients, ensuring the smooth flow of emergency channels, and making the multi-source resource scheduling arrangement in the hospital for medical emergency scenarios more scientific, reasonable and orderly. In addition, during operation, the system can automatically match the nearest operating room, dynamically adjust the capture range of medical staff, optimize medical staff according to the tendency value, control the elevator to stop at the specified floor, quickly build the path topology within the hospital, and synchronously display medical staff on the path. It also plays the prompt tone through the speaker in a loop to guide the movement, realizing the intelligent allocation and path optimization of emergency medical resources.

[0120] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention 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 will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. An intelligent medical management system based on artificial intelligence, characterized in that: include: The sensing module is used to sense the real-time location of medical staff and emergency transport beds in the hospital; A labeling module is used to label available operating rooms in real time on the 3D topology of the hospital pathways; The decision module is used to receive the location information of medical staff and emergency transport beds perceived by the perception module and the available operating rooms annotated by the annotation module, and use the location information of medical staff and emergency transport beds and the available operating rooms to decide on the allocation of medical staff and the path for the emergency transport beds to move to the available operating rooms; A visualization module is used to interact with all public area displays in the hospital, obtain the path of the emergency transport bed moving to the available operating room output by the decision module, display the path of the emergency transport bed moving to the available operating room on all public area displays, and indicate the path direction with an arrow icon on the displayed path of the emergency transport bed moving to the available operating room; Global warning module, used to play warning audio; Among them, the early warning audio stores voice audio that reminds people in the hospital to evacuate and keep the roads clear.

2. The intelligent medical management system based on artificial intelligence according to claim 1, characterized in that: The emergency transport bed in the sensing module is a bed used to transport patients who need immediate medical treatment or are transported by ambulance due to sudden illness; The sensing module is integrated with a number of position sensors. Each of the medical staff and emergency transport beds in the hospital is equipped with at least one sensing module. When sensing position information, the sensing module uses any position in the hospital as a reference origin coordinate and outputs its own position information. A construction unit is provided inside the perception module, and the construction unit is used to upload the location information of each path segment within the hospital and use the location information of the path within the hospital to construct a three-dimensional topology of the path within the hospital; Among them, all location information perceived by the perception module is represented on the three-dimensional topology of the hospital path. All perception modules configured for medical staff are in standby state, and all perception modules configured for emergency transport beds are in real-time operation state. When any perception module configured for emergency transport beds perceives that its own position has changed, it triggers all perception modules configured for medical staff to switch to real-time operation state.

3. The intelligent medical management system based on artificial intelligence according to claim 1, characterized in that: The operating rooms are all marked on the three-dimensional topology of the hospital path, and the system end user manually switches the text labels of the operating rooms in real time through the marking module. The lower level of the marking module is provided with a monitoring unit, which is used to monitor the operating status of the perception module configured for medical staff in real time. When the perception module is detected to be in real-time operation, the emergency transport bed is synchronously matched with the operating room; The matching logic between emergency transport beds and operating rooms is expressed as follows: Based on the perception module, the location information of the emergency transport bed is obtained in real time, the operating room closest to the location information of the emergency transport bed based on the three-dimensional topology of the intra-hospital path is identified, and the identified operating room is matched with the emergency transport bed.

4. The intelligent medical management system based on artificial intelligence according to claim 1, characterized in that: The decision module runs the received available operating room marked by the marking module, that is, the operating room identified by the monitoring unit and then matched with the emergency transport bed; The path for the emergency transport bed to move to the available operating room determined by the decision module is: the intra-hospital path used to determine the matching result between the operating room and the emergency transport bed, from the matching result between the emergency transport bed and the operating room obtained by the monitoring unit; Among them, an interactive unit is set inside the decision module, and the interactive unit is used to feedback the path of the emergency transport bed decided by the decision module during the operation phase to the available operating room to the operating room to the marking module. The marking module marks the operating room as occupied on the three-dimensional topology of the hospital path.

5. The intelligent medical management system based on artificial intelligence according to claim 1, characterized in that: The decision logic for medical staff allocation in the decision module follows: Identify the path of the emergency transport bed to the available operating room on the three-dimensional topology of the hospital path, and simultaneously set the medical staff capture range. Use the medical staff capture range as the radius and all points on the path of the emergency transport bed to the available operating room as the origin to determine the medical staff capture area. Combined with the in-hospital medical staff location information perceived by the perception module, all medical staff within the medical staff capture area are obtained. The demand for medical staff is set, the medical staff allocation tendency values ​​obtained in the medical staff capture area are analyzed, and the medical staff are arranged in descending order based on the tendency values. The medical staff corresponding to the set medical staff demand are selected at the front position in the descending medical staff queue as the medical staff allocation result.

6. The intelligent medical management system based on artificial intelligence according to claim 5, characterized in that: The decision module is provided with a reset unit at the lower level, which is used to refresh the decision logic of the medical staff configuration in the decision module; Among them, when the decision module refreshes the operation through the reset unit, the set medical staff capture range is increased to 3 / 2 of the original medical staff capture range, and so on, until the number of medical staff included in the descending medical staff queue is not less than the medical staff demand.

7. The intelligent medical management system based on artificial intelligence according to claim 5, characterized in that: During the operation phase of the decision module, it interacts with each elevator in the hospital and controls the operation of each elevator so that on all sections of the path where the emergency transport bed is moved to the available operating room, there is at least one elevator corresponding to each section that is located on the floor corresponding to the indication on the path where the emergency transport bed is moved to the available operating room.

8. The intelligent medical management system based on artificial intelligence according to claim 5, characterized in that: The medical staff configuration propensity value analysis logic is expressed as: ； Where: Assign propensity scores to healthcare workers; The medical staff demand level in the area corresponding to the medical staff's location; The shortest straight-line distance from the location of the medical staff to the path of the emergency transport bed to the available operating room; For medical staff The path distance from the medical staff's location to the end point of the path for the emergency transport bed to move to the available operating room after the path reaches the path for the emergency transport bed to move to the available operating room; Online hours for healthcare workers; Among them, medical staff online time That is, the current cumulative continuous working hours of medical staff, The intensive care unit is the first level, the inpatient convalescent unit is the second level, the inspection and medication distribution unit is the third level, and other hospital areas are the fourth level. The larger it is, the more suitable the medical staff is to be selected as the medical staff included in the medical staff configuration results.

9. The intelligent medical management system based on artificial intelligence according to claim 1, characterized in that: During the operation phase of the visualization module, all selected medical staff are synchronously displayed on the path of the emergency transport bed moving to the available operating room on the display in the public area, that is, the medical staff configuration result. The perception module configured in the medical staff is also integrated with a speaker, and the speaker stores prompt audio. During the operation phase of the visualization module, the speaker integrated in the perception module of the selected medical staff is synchronously triggered to play the prompt audio in a loop; Among them, the medical staff corresponding to the sensing module where all the speakers playing the prompt audio are located read the path and direction of the emergency transport bed moving to the available operating room based on the display in the public area of ​​the hospital, and move along the path and direction. If they encounter an elevator, they confirm whether the elevator is on the current floor; If the elevator is on the current floor, it will wait; if the elevator is not on the current floor, it will continue to move; If you encounter an elevator again, perform the above operations again.

10. The intelligent medical management system based on artificial intelligence according to claim 1, characterized in that: The perception module is interactively connected to a construction unit via a wireless network, the perception module is interactively connected to the labeling module via a wireless network, the labeling module is interactively connected to a monitoring unit at a lower level via a wireless network, the monitoring unit is interactively connected to the perception module via a wireless network, the labeling module is interactively connected to a decision module via a wireless network, the decision module is interactively connected to an interaction unit via a wireless network, the interaction unit is interactively connected to the labeling module via a wireless network, the decision module is interactively connected to a reset unit at a lower level via a wireless network, and the decision module is interactively connected to a visualization module and a global warning module via a wireless network.

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