Disease prevention and management system based on image recognition and big data

By adopting distributed storage and parallel processing technology in the disease prevention management system, personalized adjustment of the prediction model with individual differences, and establishing a closed-loop feedback mechanism, the problems of inaccurate image feature extraction and low efficiency of big data processing in the existing technology are solved, and high accuracy and personalized disease prediction effects are achieved.

CN119786022AInactive Publication Date: 2025-04-08CHONGQING ZHIHAN TECH CO LTD +1
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Patent Information

Application Number
CN202510275200.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-10
Publication Date
2025-04-08
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Existing image recognition technology cannot accurately extract key feature information in images, resulting in inaccurate disease prediction results, low processing efficiency of big data and slow response speed, which affects the real-time and accuracy of the system. The existing prediction models cannot fully consider individual differences in patients, resulting in a lack of personalization of prediction results.

Method used

A disease prevention management system based on image recognition and big data is adopted, including an image acquisition module, a big data processing module and a feature extraction prediction module. The efficiency of big data processing is improved through distributed storage and parallel processing technology, personalized adjustments are made to the prediction model based on individual differences, and a closed-loop feedback mechanism is established to automatically adjust the image acquisition and analysis strategy.

Benefits of technology

It improves the accuracy of image feature extraction, improves the efficiency of big data processing, realizes the personalization of the prediction model, enhances the real-time and accuracy of the system, and improves the system's self-optimization and continuous improvement capabilities through the closed-loop feedback mechanism.

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Abstract

A disease prevention and management system based on image recognition and big data, specifically relates to the technical field of disease prevention and management of image recognition. The scheme includes an image acquisition module for acquiring image information of the current patient and converting the acquired analog signal into a digital signal. The big data processing module is used to adopt the distributed storage and parallel processing technology of big data to extract data information of the same gender and age group, and to perform disease prediction evaluation according to the normal interval and severe interval of the disease prediction severity score PF of the same gender and age group, and collect and manage after the evaluation. The feature extraction and prediction module calculates and outputs the preliminary evaluation value QT of the image feature, the abnormal area feature value YT, and the disease prediction severity score PF in sequence. The feedback display module is used to display the severity of the disease prediction. The present invention can more accurately evaluate the health status of the patient and provide a scientific basis for the prevention and management of the disease.
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