A health risk early warning method based on artificial intelligence
By using a deep learning-based health risk early warning model and multi-parameter health monitoring equipment for data collection and analysis, the problem of high false alarm and false negative rates in existing systems has been solved. This enables accurate and personalized health risk early warning and management recommendations, providing forward-looking and personalized health management services.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHANGSHI CLOUD TECHNOLOGY DEVELOPMENT (ANHUI) CO LTD
- Filing Date
- 2026-01-29
- Publication Date
- 2026-06-05
AI Technical Summary
Existing health monitoring systems cannot effectively utilize multi-dimensional time-series data, ignore the complex correlations between physiological parameters and individual differences, resulting in high false alarm and false negative rates and a lack of personalized health management guidance.
A health risk early warning model based on deep learning networks is adopted. Data is collected in real time through multi-parameter health monitoring devices, and the data is cleaned and standardized. Deep analysis is performed using models such as recurrent neural networks to generate personalized health risk warnings and management suggestions.
It improves the accuracy of health risk warnings, reduces false alarm and false negative rates, provides forward-looking warnings and personalized suggestions, and achieves 24-hour uninterrupted intelligent health monitoring.
Smart Images
Figure CN122158107A_ABST