Intelligent home metabolic disease diagnosis and treatment management system based on Internet hospital

Abstract

The invention relates to the technical field of data management, and discloses a smart home metabolic disease diagnosis and treatment management system based on an internet hospital, and the system comprises a multi-source data collection terminal which is used for collecting blood glucose level, blood fat data and uric acid parameters, the collected data are uploaded to the cloud intelligent analysis platform; and the cloud intelligent analysis platform receives the data uploaded by the multi-source data acquisition terminal and performs standardization processing on the data. The multi-source data acquisition terminal and the encryption transmission technology are adopted, blood glucose, blood fat and uric acid can be acquired in real time, the data are uploaded to the cloud intelligent analysis platform, compared with an existing manual monitoring or single data acquisition mode, comprehensive health data can be efficiently and safely acquired, human intervention and data distortion are reduced, and the safety of health monitoring is improved. And the accuracy and the real-time performance of data acquisition are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data management, in particular to an intelligent home metabolic disease diagnosis and treatment management system based on an Internet hospital. BACKGROUND

[0002] In recent years, the population aging intensifies, and the incidence of metabolic diseases and related complications continues to rise.

[0003] For example, the existing public number relates to an AI-driven cardiovascular disease multi-dimensional data collaborative management system and method, which can solve the problem of data islands and non-uniformity of cardiovascular disease multi-dimensional data in the prior art. The existing public number is a cardiovascular disease assessment management system based on big data, which includes a resident end, a community hospital, a secondary hospital doctor end, a tertiary hospital doctor end, and a health authority management end. The resident end includes a basic data management system, a filing system, a daily monitoring system, a cardiovascular disease risk prediction system, a prompt system, an education system, and an exchange system.

[0004] Currently, the home chronic disease monitoring system mostly adopts a one-way early warning mode, but cannot form effective linkage with the electronic medical record system, the chronic disease follow-up platform, and the multi-disciplinary consultation mechanism, and the early warning without intervention mode is easy to cause patients to ignore the risk, increasing the possibility of disease deterioration and sudden complications.

[0005] Therefore, the present application provides an intelligent home metabolic disease diagnosis and treatment management system based on an Internet hospital to solve the above problems. SUMMARY

[0006] In view of the deficiencies of the prior art, the present application provides an intelligent home metabolic disease diagnosis and treatment management system based on an Internet hospital to solve the problems in the above background.

[0007] To achieve the above purpose, the present application realizes the following technical scheme: an intelligent home metabolic disease diagnosis and treatment management system based on an Internet hospital, characterized in that the intelligent home metabolic disease diagnosis and treatment management system comprises: a multi-source data acquisition terminal for acquiring blood glucose level, blood lipid data and uric acid parameters, and uploading the acquired data to a cloud intelligent analysis platform; a cloud intelligent analysis platform receiving data uploaded by the multi-source data acquisition terminal, performing standardized processing on the data, generating an early warning signal, and prompting potential metabolic disease risks; a hospital emergency response system receiving the early warning signal of the cloud intelligent analysis platform, dispatching medical resources, and transmitting the dispatching information to a blockchain audit system; The blockchain audit system receives and stores operation data of a multi-source data acquisition terminal, a cloud intelligent analysis platform and a hospital emergency response system, and generates an audit log; The multi-terminal collaborative diagnosis platform receives the audit log of the blockchain audit system, and provides an interactive interface of a doctor terminal, a community terminal and a patient terminal, wherein the interactive interface displays early warning signals, scheduling information and audit logs related to metabolic diseases.

[0008] The present application provides an intelligent home metabolic disease diagnosis and treatment management system based on an Internet hospital. 1、The multi-source data acquisition terminal and encryption transmission technology of the present application can collect blood glucose, blood lipids and uric acid in real time, and upload the data to the cloud intelligent analysis platform. Compared with the existing manual monitoring or single data acquisition method, the technical solution can efficiently and safely obtain comprehensive health data, reduce human intervention and data distortion, and improve the accuracy and real-time performance of data acquisition.

[0009] 2、The cloud intelligent analysis platform of the present application can generate early warning signals of metabolic diseases by standardizing the collected data and combining with the triage rule engine. Compared with the traditional static diagnosis method, the present application can dynamically and real-time identify potential risks, early warning and guide personalized intervention, and significantly improve the effectiveness of early disease detection and intervention.

[0010] 3、The hospital emergency response system of the present application can timely evaluate medical resources and dynamically schedule after receiving the early warning signals of the cloud platform, ensure the efficient use of medical resources, and compared with the existing manual scheduling and resource management method, the present application improves the response speed and resource utilization efficiency, avoids resource waste or response lag, and enhances the flexibility and accuracy of emergency response.

[0011] 4、The blockchain audit system of the present application is used to store and verify operation data of each link, ensure the non-tamperability and security of data, and compared with the traditional data storage and audit method, the present application effectively prevents data tampering through blockchain technology, ensures the transparency and reliability of data, and provides a credible record and audit path for medical management.

[0012] 5、The multi-terminal collaborative diagnosis platform of the present application ensures the real-time interaction and information sharing of the doctor terminal, the community terminal and the patient terminal, improves the collaborative efficiency of the diagnosis and treatment process, compared with the existing single platform or isolated diagnosis and treatment mode, the present application promotes the efficient cooperation of all parties, optimizes the diagnosis and treatment decision, improves the accuracy and individualization of the treatment scheme, and helps to improve the treatment effect and satisfaction of patients. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 The system diagram of the present application; Figure 2 This is a schematic diagram of the multi-source data acquisition terminal of the present invention; Figure 3 This is a schematic diagram of the cloud-based intelligent analysis platform of the present invention; Figure 4 This is a schematic diagram of the hospital emergency response system of the present invention; Figure 5 This is a schematic diagram of the blockchain auditing system of the present invention; Figure 6 This is a schematic diagram of the multi-terminal collaborative diagnostic platform of the present invention. Detailed Implementation

[0014] To enable those skilled in the art to understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort should fall within the scope of protection of the present invention.

[0015] The present invention will now be described in detail with reference to the accompanying drawings: Example: Please see the appendix Figure 1 -Appendix Figure 6 This invention provides an intelligent home-based metabolic disease diagnosis and treatment management system based on an internet hospital. The intelligent home-based metabolic disease diagnosis and treatment management system includes: A multi-source data acquisition terminal is used to collect blood glucose levels, blood lipid data, and uric acid parameters, and uploads the collected data to a cloud-based intelligent analysis platform; The blood glucose measurement unit measures and records the concentration of glucose in the blood. It uses an enzyme current method for measurement, and the enzyme current formula is as follows: , in, The measured current value is proportional to the glucose concentration; This refers to the glucose concentration. It is the calibration coefficient; The sensor voltage; The blood lipid analysis unit is used to analyze the lipid components in the blood. The blood lipid analysis unit uses spectral absorption method for analysis, and the spectral absorption formula is as follows: , in, Absorbance; The molar absorptivity of blood lipids; Blood lipid concentration; The optical path length of the sample; The uric acid detection unit is used to detect the uric acid level, and the electrochemical detection method is adopted to judge the uric acid concentration through the potential difference, and the formula is: , Among them, is the potential difference; is the uric acid concentration; is the gas constant; is the absolute temperature; is the charge number; is the Faraday constant; and are the external and internal uric acid concentrations; The data transmission unit is used to upload the data collected by the above-mentioned units to the cloud intelligent analysis platform, and the data transmission process is securely transmitted through the encryption algorithm, and the encryption formula is : , Among them, is the encrypted data; is the original collected data; is the encryption index; is the modulus; The cloud intelligent analysis platform receives the data uploaded by the multi-source data collection terminal, processes the data, generates an early warning signal, and prompts the potential metabolic disease risk; The data receiving unit is used to receive the blood glucose level, blood lipid data and uric acid parameters uploaded by the multi-source data collection terminal; The received data is formatted as: , wherein, is the blood glucose level, is the blood lipid data, is the uric acid level; The data processing unit is used to standardize the received original data to eliminate the differences in units and ranges; The standardization formula in the processing process is: , Among them, is the mean of the sample, is the standard deviation of the sample, is the standardized data; The triage rule engine unit is used to identify the potential metabolic disease risk according to the standardized data ; The analysis engine generates an early warning signal according to a specific threshold, and the calculation formula is: , wherein, is the blood glucose level, is the blood lipid data, is the uric acid level; unit, the early warning signal output by the integrated data processing unit and the patient's historical health data to determine whether to trigger an early warning; the judgment condition is realized by a rule set function : , wherein, is the decision rule set, is the risk prediction value, is the historical health data; early warning generation unit, for generating risk prediction value generated by the unit generate an early warning signal, then prompt the potential risk of metabolic disease, and then upload the early warning signal to the hospital emergency response system to inform relevant medical resources to prepare; hospital emergency response system, receiving the early warning signal of the cloud intelligent analysis platform, dispatching medical resources, and transmitting the dispatching information to the blockchain audit system; early warning receiving unit, for receiving the early warning signal from the cloud intelligent analysis platform, the early warning signal prompting the possible risk of metabolic disease; The early warning receiving unit filters redundant information through a signal processing algorithm to ensure response efficiency, and the signal processing formula is: , wherein, is the processed early warning signal, is the signal processing function, is the time window parameter; resource assessment unit, for assessing the currently available medical resources according to the received early warning signal , and the resource assessment calculation formula is: , wherein, is the current resource amount, is the total amount of resources, is the amount of existing resource usage; dispatching decision unit, for determining the resource data provided by the resource assessment unit and the emergency degree of the early warning signal , make medical resource scheduling strategy, decision algorithm is: , Among them, is the scheduling decision result, is the determination threshold of the emergency degree, is the minimum resource requirement; Information transmission unit, upload the results of scheduling decision unit And related details to the blockchain audit system; Information transmission uses encryption algorithm to ensure security, and the encryption formula is: , Among them, is the encrypted scheduling information, is the encryption function, is the original information, is the encryption key; Blockchain audit system, receive and store the operation data of multi-source data acquisition terminal, cloud intelligent analysis platform and hospital emergency response system, generate audit log; Data verification receiving unit, used for receiving and verifying the operation data from multi-source data acquisition terminal, cloud intelligent analysis platform and hospital emergency response system; The receiving unit processes the data integrity through the data verification formula: , Among them, is the check value, is the hash function, is the received data; Data storage unit, used for storing the verified operation data; Adopt chain structure to save data, and ensure the data tamper resistance through blockchain technology, the formula is: , Among them, is the current block data structure, is the current data, is the hash value of the previous block, is the time stamp; Audit log generation unit, responsible for generating audit log based on blockchain, used to track and record the history of each operation, the generation formula is as follows: , Among them, is the audit log, is the Block data, is the total block number of operation data; The security monitoring unit monitors the security of the blockchain system and detects abnormal operations in real time. If an anomaly is detected, an alarm is triggered, and the determination formula is as follows: , in, Alarm status. This is an abnormal operation detection value. This is the threshold for anomaly detection; The multi-terminal collaborative diagnostic platform receives audit logs from the blockchain audit system and provides interactive interfaces for doctors, communities, and patients. The interactive interfaces display early warning signals, scheduling information, and audit logs related to metabolic diseases. The log receiving unit receives audit logs transmitted by the blockchain audit system. It interprets the audit logs using log parsing formulas for subsequent processing. , in, The parsed log data, For analytic functions, For audit logs; The information display unit is used to display the data parsed by the log receiving unit on the interactive interfaces of doctors, communities, and patients. Including warning signals related to metabolic diseases Scheduling information and audit logs The display format formula is: , in, For the information set to be displayed, To demonstrate formatting functions, For user interface parameters; The interactive analysis unit optimizes treatment strategies through user feedback and log data analysis. The analysis process uses a user feedback coefficient to assess diagnostic accuracy; the analysis formula is as follows: , in, For interactive analysis results, User feedback coefficient Number of user samples; The diagnostic decision support unit combines the results of the interactive analysis unit. Provides decision-making suggestions to doctors, optimizes treatment plans, and the decision support is based on a weighted model formula: , in, To provide suggestions for decision support, This is a weighting factor for the treatment plan.

[0016] Multi-source data collection terminal, through the integration of real-time monitoring of blood glucose, blood lipids and uric acid, realizes comprehensive and timely tracking of metabolic diseases. By using enzyme current method, spectral absorption method and electrochemical detection method, the measurement results provide data basis for cloud analysis. The data is uploaded to the cloud immediately after collection, providing seamless connection for the next analysis and decision-making, greatly improving the diagnosis efficiency of remote medical treatment.

[0017] Cloud intelligent analysis platform, through the standardized processing of multi-source data, eliminates the data deviation caused by equipment difference, ensures the accuracy and consistency of analysis. The cloud analysis platform can automatically generate early warning signals, and can identify potential metabolic disease risks through deep analysis of data, effectively reduce the risk of missed diagnosis and misdiagnosis, provide data support for timely intervention, and improve the accuracy of clinical diagnosis.

[0018] Hospital emergency response system, through rapid dispatching of medical resources and transmission of information to the blockchain audit system, realizes efficient use of medical resources. The emergency response system can improve the reaction speed of the hospital to emergency situations, and ensure the safety of information transmission process. Through seamless connection with the cloud analysis platform, the medical institutions can quickly respond to the sudden risk of metabolic diseases, and ensure that patients receive necessary medical treatment in the first time.

[0019] Blockchain audit system, ensures the non-tamperability of operation data, has strong security features, realizes the reliability of data transmission and storage. The application of blockchain technology enhances the transparency of data audit, and ensures the security and integrity of the system. Through real-time monitoring and generating audit logs, the system provides effective technical support for supervision and security traceability, which helps to maintain the privacy of patients and the integrity of data.

[0020] Multi-terminal collaborative diagnosis platform, through providing multi-directional interactive interface, doctors, communities and patients can access and participate in disease management at the same time. The system supports real-time early warning signal display, dispatching information transmission and audit log viewing, enhances information transparency and collaboration efficiency. Through user feedback feedback mechanism and data analysis, continuously optimize diagnosis and treatment strategies, provide scientific decision-making basis for doctors, improve the accuracy and effectiveness of diagnosis and treatment.

[0021] Although the embodiments of the present application have been shown and described, it can be understood by those skilled in the art that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. An intelligent home-based metabolic disease diagnosis and treatment management system based on an Internet hospital, characterized in that, The system comprises: A multi-source data collection terminal for collecting blood glucose level, blood lipid data and uric acid parameters, and uploading the collected data to a cloud intelligent analysis platform, comprising: A cloud intelligent analysis platform receiving data uploaded by the multi-source data collection terminal, performing standardized processing on the data, generating an early warning signal, and prompting potential metabolic disease risks, comprising: A data receiving unit for receiving blood glucose level, blood lipid data and uric acid parameters uploaded by the multi-source data collection terminal; a data processing unit for normalizing the received raw data standardization processing; triage rules engine unit for identifying potential metabolic disease risk identifying potential metabolic disease risk; The analysis engine generates a warning signal depending on a specific threshold value The calculation formula is: ， wherein, is a blood glucose level, is a blood lipid data, is a uric acid level; unit, integrating the early warning signal output by the data processing unit and historical health data of the patient to decide whether an early warning needs to be triggered; Judgment condition by rule set function Implementation: ， wherein, is a decision rule set, is a risk prediction value, is historical health data; The early warning generation unit is configured to generate an early warning signal based on the risk prediction value The risk prediction value generated by the unit The early warning signal is generated to prompt the potential metabolic disease risk, and the early warning signal is uploaded to a hospital emergency response system to notify relevant medical resources to prepare. 2.The intelligent home-based metabolic disease diagnosis and treatment management system based on an Internet hospital of claim 1, wherein, The multi-source data collection terminal further comprises: Data transmission unit for uploading the data collected by the above-mentioned units to the cloud intelligent analysis platform, and the data transmission process is securely transmitted through an encryption algorithm, and the encryption formula is : ， wherein, is the encrypted data; is the original collected data; is the encryption exponent; is the modulus. 3.The intelligent home-based metabolic disease diagnosis and treatment management system based on an Internet hospital of claim 2, characterized in that, The multi-source data collection terminal comprises: A blood glucose measurement unit for measuring and recording glucose concentration in blood, the blood glucose measurement unit uses enzyme current method for measurement The enzyme current formula is: ， wherein, is the measured current value, proportional to the glucose concentration; is the glucose concentration; is the calibration factor; is the sensor voltage; A blood lipid analysis unit for analyzing fat components in blood, the blood lipid analysis unit uses spectrum absorption method for analysis, and the spectrum absorption formula is: ， wherein, is the absorbance; is the molar absorption coefficient of the blood lipid; is the blood lipid concentration; is the sample optical path length; A uric acid detection unit for detecting uric acid level, the uric acid detection unit uses electrochemical detection method to determine uric acid concentration through potential difference, and the formula is: ， wherein, is the potential difference; is the uric acid concentration; is the gas constant; is the absolute temperature; is the charge number; is the Faraday constant; and are the external and internal uric acid concentrations. 4.The intelligent home metabolic disease diagnosis and treatment management system based on an Internet hospital according to claim 1, characterized in that, The system further comprises a hospital emergency response system receiving the early warning signal of the cloud intelligent analysis platform, dispatching medical resources, and transmitting the dispatching information to a blockchain audit system, comprising: Early warning receiving unit, for receiving early warning signals from the cloud intelligent analysis platform Early warning signals Prompt possible metabolic disease risk; the early warning receiving unit filters redundant information through a signal processing algorithm, ensures response efficiency, and the signal processing formula is: ， wherein, is the processed early warning signal, is the signal processing function, is the time window parameter. 5.The intelligent in-home metabolic disease diagnosis and treatment management system based on an Internet hospital of claim 4, wherein, The hospital emergency response system further comprises: a resource assessment unit configured to assess available medical resources based on the received warning signal assessing currently available medical resources using a resource assessment formula ， wherein, is the currently allocable resource amount, is the total resource amount of the hospital, is the existing resource usage amount; The scheduling decision unit is used to make decisions based on the resource data provided by the resource assessment unit. and the urgency of the warning signal A medical resource allocation strategy is formulated, and the decision-making algorithm is as follows: ， wherein, is a scheduling decision result, is an emergency degree determination threshold value, is a minimum resource amount requirement; information transmission unit, which transmits the result of the dispatch decision unit and related details to a blockchain audit system and related details to a blockchain audit system; The information transmission uses an encryption algorithm to ensure security, and the encryption formula is: ， wherein, is encrypted scheduling information, is an encryption function, is original information, is an encryption key. 6.The intelligent in-home metabolic disease diagnosis and treatment management system based on an Internet hospital of claim 1, wherein, The system further comprises a blockchain audit system receiving and storing operation data of the multi-source data collection terminal, the cloud intelligent analysis platform and the hospital emergency response system, generating an audit log, comprising: A data verification receiving unit for receiving and verifying operation data from the multi-source data collection terminal, the cloud intelligent analysis platform and the hospital emergency response system; The receiving unit processes data integrity through a data verification formula: ， wherein, is a check value, is a hash function, is the received data; A data storage unit for storing verified operation data; A chain structure is used to save data, and the blockchain technology is used to ensure the non-tamperability of data, and the formula is: ， wherein, is a current block data structure, is current data, is a hash value of a previous block, is a timestamp. 7.The intelligent home-based metabolic disease diagnosis and treatment management system based on an Internet hospital of claim 6, wherein, In the blockchain audit system, further comprising: An audit log generation unit responsible for generating an audit log based on the blockchain to track and record the history of each operation, and the generation formula is as follows: ， wherein, is an audit log, is a first is a block data, is a total number of blocks of operation data; A security monitoring unit for monitoring the security of the blockchain system and detecting abnormal operations in real time; if an abnormality is detected, an alarm is triggered, and the determination formula is: ， wherein, is an alarm state, is an abnormal operation detection value, is an abnormality detection threshold value. 8.The intelligent in-home metabolic disease diagnosis and treatment management system based on an Internet hospital of claim 1, wherein, In the multi-terminal collaborative diagnosis platform, further comprising: A log receiving unit for receiving the audit log transmitted by the blockchain audit system, and the log receiving unit interprets the audit log through a log analysis formula for subsequent processing: ， wherein, is parsed log data, is a parsing function, is an audit log; An information display unit is configured to display data parsed by the log receiving unit on a doctor terminal, a community terminal, and a patient terminal , including early warning signals related to metabolic diseases , dispatch information , and audit logs , and the display format is as follows: ， wherein, is a set of information for presentation, is a presentation format function, is a user interface parameter. 9.The intelligent in-home metabolic disease diagnosis and treatment management system based on an Internet hospital of claim 1, wherein, The system further comprises a multi-terminal collaborative diagnosis platform receiving the audit log of the blockchain audit system, providing an interactive interface for the doctor end, the community end and the patient end, and the interactive interface displays the early warning signal, the dispatching information and the audit log related to metabolic diseases, comprising: An interactive analysis unit for optimizing diagnosis and treatment strategies through user feedback and log data analysis, and a user feedback coefficient is used to evaluate the accuracy of diagnosis in the analysis process, and the analysis formula is: ， wherein, is the interaction analysis result, is the user feedback coefficient, is the number of user samples; A diagnosis and treatment decision support unit combines the results of the interaction analysis unit The decision support for the doctor side provides decision suggestions, optimizes treatment plans, and is based on a weight model formula: ， wherein, is a decision support recommendation, is a treatment regimen weight factor.

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