CN114678126A - Disease tracking and predicting system - Google Patents
Disease tracking and predicting system Download PDFInfo
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- CN114678126A CN114678126A CN202210262576.XA CN202210262576A CN114678126A CN 114678126 A CN114678126 A CN 114678126A CN 202210262576 A CN202210262576 A CN 202210262576A CN 114678126 A CN114678126 A CN 114678126A
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Abstract
The invention relates to a disease tracking and predicting system, which comprises: the data acquisition tracking module adopts a cloud database server, records personal information, medical history and health data of a user through information sensing equipment, and the information sensing equipment is connected with the cloud database server through a 5G network and forms a prediction and tracking model through long-term monitoring; the data analysis module is used for sending data in the cloud database to the hospital database, inputting data related to disease risk factors into a risk prediction model, and establishing the disease prediction model through big data analysis and machine learning; and the evaluation application module classifies and arranges the data and carries out standardized processing to generate a disease trend report, and informs the analysis result and the early warning to the user through a computer, a tablet or a mobile phone. The invention analyzes the illness state through the integral integration and coordination of the collected and tracked data, thereby reminding medical care personnel to timely diagnose and track the rehabilitation condition of the patient and predicting the possible diseases.
Description
Technical Field
The invention relates to a disease tracking and predicting system, and belongs to the field of medical data management.
Background
However, the existing disease tracking and predicting method has the problem that although the existing equipment can record the information of the patient, the existing equipment cannot analyze the disease condition through the integral integration and coordination of the collected and tracked data, so that medical staff are reminded to follow the patient and track the recovery condition of the patient in time, and the possible disease can be predicted.
Disclosure of Invention
The invention aims to provide a disease tracking and predicting system, which solves the problems that the existing disease tracking and predicting method cannot analyze the disease condition through integral integration and coordinated acquisition and tracking data, so that medical workers are reminded to make a follow-up visit in time, the recovery condition of a patient is tracked, and the possible diseases are predicted.
In order to solve the technical problem, the invention adopts a technical scheme that: a disease tracking prediction system comprising:
the data acquisition tracking module adopts a cloud database server, records personal information, medical history and health data of a user through information sensing equipment, and the information sensing equipment is connected with the cloud database server through a 5G network and forms a prediction and tracking model through long-term monitoring;
The data analysis module is used for sending data in the cloud database to the hospital database, inputting data related to disease risk factors into a risk prediction model, and establishing the disease prediction model through big data analysis and machine learning;
and the evaluation application module classifies and arranges the data and carries out standardized processing to generate a disease trend report, and informs the analysis result and the early warning to the user through a computer, a tablet or a mobile phone.
The information sensing equipment comprises a pedometer, a bracelet heart rate belt, an intelligent blood glucose meter, an intelligent watch and other similar equipment.
In order to facilitate understanding of a user, the analysis result and the early warning of the data analysis module are sent to the user in a visual chart form.
The collected and tracked health data comprises infectious disease registration information, health sign monitoring data, risk population journey records, medication records, past medical history, blood routine characteristic data, urine routine characteristic data, tumor characteristic data, blood flow characteristic data, blood biochemical characteristic data, occupational disease data, gene data, life style and work and rest time.
The information pushed by the evaluation application module comprises the types, dosage and prompting reminding of medication and the suggestion of changing the life style of the medicine.
Further, an iterative lifting under-sampling model is adopted in the disease prediction model, USIB iteratively performs under-sampling from most samples, a plurality of groups of weak classifiers are constructed, a strong classifier is integrated in a weighted combination mode, and finally the prediction label is selected and optimized based on the maximum mutual information tree of the label, so that the disease prediction is realized. The disease prediction model may also employ neural network techniques.
The system architecture of the cloud database comprises an infrastructure layer, a data supporting layer, a software supporting layer and an application layer; the basic facility layer consists of a computer and a storage device thereof, a basic operating system, a communication facility, an application server and a database management system; the data support layer comprises management and storage in aspects of information tracking data, internet information data, system management data and the like; the software supporting layer comprises an upper layer operation for providing basic function service and processing related general information; the application processing layer comprises a main information acquisition and management component, an information pushing component, a data processing component and a system management component.
Compared with the prior art, the invention has the following advantages:
1. the illness state is analyzed through the integral integration and the coordinated acquisition and tracking of data, so that medical staff are reminded to timely diagnose and track the rehabilitation condition of a patient at any time, and the possible diseases are predicted.
2. The operation is simple and flexible, the system is stable, and the user can operate the system at any place with a network without the limitation of regions.
3. The management ability of the user on the health state of the user is improved, medicine changes are made according to the change of physical indexes, and living habits and behavior modes are guided on the other hand.
4. The hospital can quickly acquire the illness state information of the patient, follow up the illness state of the patient and improve the efficiency of seeing a doctor.
5. And identifying high risk groups and carrying out risk factor intervention.
Detailed Description
The invention is further described below:
a disease tracking prediction system comprising: the data acquisition tracking module adopts a cloud database server, records personal information, medical history and health data of a user through information sensing equipment, and the information sensing equipment comprises a pedometer, a bracelet heart rate belt, an intelligent glucometer or an intelligent watch. The operation of the information sensing equipment is simple and flexible, the system is stable, and a user can operate the system in any place with a network without the limitation of regions. And high risk groups can be identified for risk factor intervention.
The collection and the detection of diseases in the synchronous database can be realized by using the internet data capture technology, and the task of information collection is completed by combining the manual participation and the intelligent information collection.
The system architecture of the cloud database comprises four levels, namely an infrastructure layer, a data supporting layer, a software supporting layer and an application layer. The infrastructure layer is composed of a computer and a storage device thereof, a basic operating system, a communication facility, an application server, a database management system and the like, and is mainly used for dynamic tracking of internet information for disease monitoring. The key of the data support layer is to manage and store the internet information data (mainly including information tracking data, internet information data, system management data and the like). The main existing forms are as follows: subject word bank, internet resource bank, security management, subject bank, word network bank, management bank and system management bank. The software supporting layer comprises middleware and a kit tool, and mainly provides basic function service and related general information processing for upper layer operation, and the layer mainly provides services such as internet information capture, full-text retrieval, domain knowledge processing and information visualization display. The application processing layer is used as the main part of the system architecture and is combined with the basic service and compiling service logic processing module of the lower layer as a support to realize the service function and service of the system. The system mainly comprises a main information acquisition and management component, an information pushing component, a data processing component and a system management component.
The information sensing equipment is connected with a cloud database server through a 5G network, and a prediction and tracking model is formed through long-term monitoring; the collected and tracked health data comprises infectious disease registration information, health sign monitoring data, risk group journey records, medication records, past medical history, blood routine characteristic data, urine routine characteristic data, tumor characteristic data, blood rheology characteristic data, blood biochemical characteristic data, occupational disease data, gene data, life style and work and rest time.
The information sensing equipment connected with the 5G network comprises a sensing layer, a network layer and an application layer, wherein the sensing layer comprises a camera, a two-dimensional code, various sensors and other sensing terminals and is mainly used for collecting various types of health data. The technologies employed include RFID (radio frequency identification), EPC (electronic code), and the like.
The information sensing equipment is connected with the Internet to construct a large-scale network, and the information sensing equipment closely links resources through the medical Internet of things technology, so that resource intercommunication and information sharing are realized.
The data analysis module is used for sending data in the cloud database to a hospital database, inputting data related to disease risk factors into a risk prediction model, and establishing the disease prediction model through big data analysis and machine learning;
Disease prediction is one of the most effective measures for achieving chronic disease management, and in recent years, mathematical models have been used for prediction of various diseases by improving disease prediction models. The disease prediction model adopts an iteration lifting under-sampling model, USIB iteratively performs under-sampling from most samples, a plurality of groups of weak classifiers are constructed, a strong classifier is integrated in a weighted combination mode, and finally, the prediction label is selected and optimized based on the maximum mutual information tree of the label, so that the disease prediction is realized.
The disease prediction model is obtained by adopting a neural network technology and pre-training a BP neural network model.
And the evaluation application module classifies and arranges the data and carries out standardized processing to generate a disease trend report, and informs the analysis result and the early warning to the user through a computer, a tablet or a mobile phone. The analysis result and the early warning of the data analysis module are sent to the user in a visual chart form, so that the management capability of the user on the health state of the user is improved, medicine changes are made according to changes of body indexes, and living habits and behavior modes are guided on the other hand. And can initiatively follow up infectious disease risk crowd's health every day, gather information and can discover the abnormal conditions in the very first time according to medical personnel's demand, contact patient and hospital fast, the very first time is handled, has effectively reduced infectious disease spreading risk, has reduced the manual work volume, under the prerequisite of guaranteeing that the information is accurate, makes medical personnel manage the operating time of oneself better, improves work efficiency.
The information pushed by the evaluation application module comprises recommended medicament types, dosage, prompting reminding of medication and recommendation of life style change.
It will be understood that the above embodiments are merely exemplary embodiments adopted to illustrate the principles of the present invention, and the present invention is not limited thereto. It will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the spirit and scope of the invention, and such modifications and improvements are also considered to be within the scope of the invention.
Claims (8)
1. A disease tracking prediction system, comprising:
the data acquisition tracking module adopts a cloud database server, records personal information, medical history and health data of a user through information sensing equipment, and the information sensing equipment is connected with the cloud database server through a 5G network and forms a prediction and tracking model through long-term monitoring;
the data analysis module is used for sending data in the cloud database to a hospital database, inputting data related to disease risk factors into a risk prediction model, and establishing the disease prediction model through big data analysis and machine learning;
and the evaluation application module classifies and arranges the data and carries out standardization processing to generate a disease trend report, and informs the analysis result and the early warning to a user through a computer, a tablet or a mobile phone.
2. The disease tracking prediction system of claim 1, wherein the information sensing device comprises a pedometer, a bracelet heart rate belt, a smart glucometer, or a smart watch.
3. The disease tracking prediction system of claim 1 wherein the analysis results and the alerts of the data analysis module are sent to the user in the form of visual charts.
4. The disease tracking and prognosis system of claim 1, wherein the collected tracked health data comprises infectious disease registration information, health sign monitoring data, risk population travel records, medication records, past medical history, blood routine characteristic data, urine routine characteristic data, tumor characteristic data, blood flow characteristic data, blood biochemical characteristic data, occupational disease data, genetic data, and lifestyle and rest times.
5. The disease tracking and prognosis system of claim 1, wherein the information pushed by the evaluation application module includes advice for using a type of medication, a dosage, a reminder to prompt for medication, and lifestyle changes.
6. The disease tracking and predicting system according to claim 1, wherein the disease prediction model employs an iterative boosting undersampling model, USIB iteratively undersamples from a plurality of types of samples, constructs a plurality of groups of weak classifiers, integrates into one strong classifier through a weighted combination mode, and finally performs selective optimization on a prediction label based on a label maximum mutual information tree to realize disease prediction.
7. The disease tracking prediction system of claim 1 wherein the disease prediction model employs neural network technology.
8. The disease tracking prediction system of claim 1 wherein the system architecture of the cloud database comprises an infrastructure layer, a data support layer, a software support layer, and an application layer; the basic facility layer consists of a computer and a storage device thereof, a basic operating system, a communication facility, an application server and a database management system; the data support layer comprises management and storage in aspects of information tracking data, internet information data, system management data and the like; the software supporting layer comprises an upper layer operation for providing basic function service and processing related general information; the application processing layer comprises a main information acquisition and management component, an information pushing component, a data processing component and a system management component.
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| CN202210262576.XA CN114678126A (en) | 2022-03-17 | 2022-03-17 | Disease tracking and predicting system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116098595A (en) * | 2023-01-16 | 2023-05-12 | 广东海纳医疗科技有限公司 | System and method for monitoring and preventing sudden cardiac death and sudden cerebral death |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116098595A (en) * | 2023-01-16 | 2023-05-12 | 广东海纳医疗科技有限公司 | System and method for monitoring and preventing sudden cardiac death and sudden cerebral death |
| CN116098595B (en) * | 2023-01-16 | 2023-09-05 | 广东海纳医疗科技有限公司 | System and method for monitoring and preventing sudden cardiac death and sudden cerebral death |
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