Big data analysis system for health and disease prevention and diagnosis
By designing a big data analysis system for health and disease prevention and diagnosis, combining big data technology and medical health knowledge, the problems of insufficient human resources and scarcity of resources for general practitioners in my country have been solved, and the accuracy and efficiency of disease diagnosis have been improved. , as well as personalized health management and medical resource optimization.
Patent Information
- Application Number
- CN202411382752.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-30
- Publication Date
- 2025-02-11
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
my country's general medical education training system is not sound, the total allocation of general practitioners' human resources is insufficient, and the capacity of health personnel is not strong, resulting in extremely limited number of family health doctors, insufficient medical staff and lack of resources, which makes it difficult to effectively help people. Health checks and disease prevention.
A big data analysis system for health and disease prevention and diagnosis was designed, combining big data technology, medical health knowledge and information technology, and using machine learning, data mining and other technologies to extract the correlation laws, abnormal patterns and prediction models in the data. Through data collection, storage, processing and diagnosis modules, an intelligent decision-making system is provided to help patients understand health status, prevent disease and first diagnosis at home or in the community.
By analyzing historical data and real-time monitoring data, potential disease risk factors and early warning signals can be discovered, the accuracy and efficiency of disease diagnosis can be improved, personalized health management and suggestions are provided, medical resource allocation can be optimized, and medical services can be improved.
Smart Images
Figure CN119418900A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the field of medical diagnosis technology, and specifically refers to a big data analysis system for health care and disease prevention and diagnosis. Background Art
[0002] With the rapid development of economy and science and technology, people's living standards have significantly improved, while the pace of life has also been accelerating. Under the influence of work pressure and lifestyle, more and more people have induced common diseases. Now, people pay more and more attention to their own health status, but my country's general medical education and training system is not sound, the total amount of general practitioner human resources is insufficient, the health personnel are not strong, the system is imperfect and the policy guarantee mechanism needs to be improved. Therefore, the number of family health doctors who can help people with examinations and guidance is extremely limited, and there are problems such as insufficient medical personnel and lack of resources.
[0003] In order to solve the above problems, the present invention aims to design an intelligent decision-making system with the knowledge of family health doctors, so that patients can understand their own health status anytime and anywhere at home or in the community through a desktop or laptop computer, prevent diseases or make a more accurate initial diagnosis of symptoms, and effectively improve the difficulty of seeing a doctor. Summary of the invention
[0004] In order to solve the above-mentioned existing problems, the present invention provides a big data analysis system for health and disease prevention and diagnosis that combines big data technology, medical health knowledge and information technology, aiming to improve the accuracy and efficiency of disease prevention and diagnosis, and optimize the overall quality and accessibility of health services.
[0005] The technical solution adopted by the present invention is as follows: The present invention is a big data analysis system for health and disease prevention and diagnosis, including a big data analysis system, a data acquisition module, a data storage module, a data processing module, a big data model module and a diagnosis module. The big data analysis system uses machine learning, data mining and other technologies to extract association rules, abnormal patterns and prediction models in the data. The data acquisition module collects medical health data in various ways. The data storage module uses a distributed computing framework to achieve efficient storage and access. The data processing module improves data quality. The big data model module uses a disease diagnosis model trained by a machine learning algorithm. The diagnosis module uses the disease diagnosis model to process the parameters provided by the data acquisition module and generate a diagnosis result.
[0006] The big data analysis system for health care and disease prevention and diagnosis includes the following steps:
[0007] S1 Data Collection: Obtain the patient's physical signs through the data collection module, and obtain symptom-based parameters through the patient's physical signs;
[0008] S2 Analyze data: Use machine learning, data mining and other technologies to extract association patterns, abnormal patterns and prediction models from data;
[0009] S3 Disease diagnosis: Input the parameters in step S1 into the big data model module, and output relevant diagnostic opinions through the diagnostic reasoning module;
[0010] S4 provides diagnosis and treatment plans: doctors use the diagnosis opinions given by S3 to assist in diagnosis and ultimately provide a diagnosis plan suitable for the patient;
[0011] S5 Follow-up visit: After a certain period of time of implementing the diagnostic plan, S1 data collection is performed again to determine the abnormal values of parameters in the diagnosis and treatment process, analyze the abnormal values to determine the effectiveness of the diagnosis, adjust the diagnostic methods that do not meet expectations, and ultimately ensure that the diagnosis and treatment plan meets expectations.
[0012] Furthermore, the data collection module includes electronic medical records and medical treatment records, equipment monitoring data, medical imaging data, genomics data, and wearable device monitoring data.
[0013] Electronic medical records and medical records: including patients’ personal information, disease diagnosis, treatment plans, medication status, and various examination and test results.
[0014] Equipment monitoring data: comes from various medical instruments such as electrocardiographs, monitors, etc., reflecting the patient's physiological condition in real time.
[0015] Medical imaging data: such as X-rays, CT, MRI, etc., provide detailed information about the internal structure of the body.
[0016] Genomic data: Gene sequence information of patients, which helps to understand the genetic mechanisms of diseases.
[0017] Wearable device monitoring data: such as heart rate monitors, blood pressure monitors, etc., provide daily health data.
[0018] Furthermore, the data processing module includes operations such as data cleaning, denoising, and standardization.
[0019] The beneficial effects achieved by the present invention using the above structure are as follows:
[0020] 1. Discover potential disease risk factors and early warning signs by analyzing historical data and real-time monitoring data.
[0021] 2. Combine clinical data and genomic data to improve the accuracy and efficiency of disease diagnosis.
[0022] 3. Provide clinical guidelines and decision support tools based on big data to help doctors develop more scientific and individualized treatment plans.
[0023] 4. Use personal health data and lifestyle information to provide personalized health management and advice.
[0024] 5. Conduct real-time monitoring and early warning of public health events such as infectious diseases and chronic diseases. BRIEF DESCRIPTION OF THE DRAWINGS
[0025] Figure 1 The structural diagram of the big data analysis system for health care and disease prevention and diagnosis proposed in this plan;
[0026] Figure 2 Flowchart of the big data analysis system structure for health care and disease prevention and diagnosis proposed for this program. DETAILED DESCRIPTION
[0027] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.
[0028] like Figure 1 and Figure 2 As shown, the big data analysis system for health care and disease prevention and diagnosis proposed in this scheme includes a big data analysis system, a data acquisition module, a data storage module, a data processing module, a big data model module and a diagnosis module. The big data analysis system uses machine learning, data mining and other technologies to extract association rules, abnormal patterns and prediction models in the data. The data acquisition module collects medical health data in various ways. The data storage module uses a distributed computing framework to achieve efficient storage and access. The data processing module improves data quality. The big data model module uses a disease diagnosis model trained by a machine learning algorithm. The diagnosis module uses the disease diagnosis model to process the parameters provided by the data acquisition module and generate a diagnosis result.
[0029] The big data analysis system for health care and disease prevention and diagnosis includes the following steps:
[0030] S1 Data Collection: Obtain the patient's physical signs through the data collection module, and obtain symptom-based parameters through the patient's physical signs;
[0031] S2 Analyze data: Use machine learning, data mining and other technologies to extract association patterns, abnormal patterns and prediction models from data;
[0032] S3 Disease diagnosis: Input the parameters in step S1 into the big data model module, and output relevant diagnostic opinions through the diagnostic reasoning module;
[0033] S4 provides diagnosis and treatment plans: doctors use the diagnosis opinions given by S3 to assist in diagnosis and ultimately provide a diagnosis plan suitable for the patient;
[0034] S5 Follow-up visit: After a certain period of time of implementing the diagnostic plan, S1 data collection is performed again to determine the abnormal values of parameters in the diagnosis and treatment process, analyze the abnormal values to determine the effectiveness of the diagnosis, adjust the diagnostic methods that do not meet expectations, and ultimately ensure that the diagnosis and treatment plan meets expectations.
[0035] The data collection module includes electronic medical records and medical treatment records, equipment monitoring data, medical imaging data, genomics data, and wearable device monitoring data.
[0036] Electronic medical records and medical records: including patients’ personal information, disease diagnosis, treatment plans, medication status, and various examination and test results.
[0037] Equipment monitoring data: comes from various medical instruments such as electrocardiographs, monitors, etc., reflecting the patient's physiological condition in real time.
[0038] Medical imaging data: such as X-rays, CT, MRI, etc., provide detailed information about the internal structure of the body.
[0039] Genomic data: Gene sequence information of patients, which helps to understand the genetic mechanisms of diseases.
[0040] Wearable device monitoring data: such as heart rate monitors, blood pressure monitors, etc., provide daily health data.
[0041] The data processing module includes operations such as data cleaning, denoising, and standardization.
[0042] Based on the patient's genetic information and clinical data, we provide personalized treatment plans, predict disease epidemic trends through big data analysis, formulate effective prevention and control strategies, analyze the prevalence and influencing factors of chronic diseases, provide a scientific basis for prevention and treatment, optimize the allocation of medical resources, and improve the efficiency and quality of medical services.
[0043] The data covers information in multiple dimensions, including structured data (such as text and tables), unstructured data (such as medical images) and time series data. With the acceleration of medical informatization, the amount of data is growing explosively. It contains rich medical knowledge and insights, and is of great value to disease prevention and diagnosis.
[0044] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.
[0045] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.
Claims
1. A big data analysis system for health and disease prevention and diagnosis, characterized by: It includes a big data analysis system, a data acquisition module, a data storage module, a data processing module, a big data model module and a diagnosis module. The big data analysis system uses machine learning, data mining and other technologies to extract correlation patterns, abnormal patterns and prediction models in the data. The data acquisition module collects medical and health data in various ways. The data storage module uses a distributed computing framework to achieve efficient storage and access. The data processing module improves data quality. The big data model module uses a disease diagnosis model trained by a machine learning algorithm. The diagnosis module uses the disease diagnosis model to process the parameters provided by the data acquisition module and generate a diagnosis result.
2. The big data analysis system for health and disease prevention and diagnosis according to claim 1 is characterized in that: The following steps are involved: S1 Data Collection: Obtain the patient's physical signs through the data collection module, and obtain symptom-based parameters through the patient's physical signs; S2 Analyze data: Use machine learning, data mining and other technologies to extract association patterns, abnormal patterns and prediction models from data; S3 Disease diagnosis: Input the parameters in step S1 into the big data model module, and output relevant diagnostic opinions through the diagnostic reasoning module; S4 provides diagnosis and treatment plans: doctors use the diagnosis opinions given by S3 to assist in diagnosis and ultimately provide a diagnosis plan suitable for the patient; S5 Follow-up visit: After a certain period of time of implementing the diagnostic plan, S1 data collection is performed again to determine the abnormal values of parameters in the diagnosis and treatment process, analyze the abnormal values to determine the effectiveness of the diagnosis, adjust the diagnostic methods that do not meet expectations, and ultimately ensure that the diagnosis and treatment plan meets expectations.
3. The big data analysis system for health and disease prevention and diagnosis according to claim 1 is characterized by: The data collection module includes electronic medical records and medical treatment records, equipment monitoring data, medical imaging data, genomics data, and wearable device monitoring data. Electronic medical records and medical records: including patients’ personal information, disease diagnosis, treatment plans, medication status, and various examination and test results. Equipment monitoring data: comes from various medical instruments such as electrocardiographs, monitors, etc., reflecting the patient's physiological condition in real time. Medical imaging data: such as X-rays, CT, MRI, etc., provide detailed information about the internal structure of the body. Genomic data: Gene sequence information of patients, which helps to understand the genetic mechanisms of diseases. Wearable device monitoring data: such as heart rate monitors, blood pressure monitors, etc., provide daily health data.
4. The big data analysis system for health and disease prevention and diagnosis according to claim 1, characterized in that: The data processing module includes operations such as data cleaning, denoising, and standardization.