Disease prediction method and system based on human immune age
By constructing an immune age prediction model based on multiple linear regression and binary logistic regression, immune biomarkers that are significantly related to age are screened out. This solves the problem of insufficient accuracy and interpretability in the existing immune age assessment, and realizes low-cost, accurate probability prediction of respiratory disease risk, supporting personalized intervention in health management.
Patent Information
- Application Number
- CN202511629552.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-07
- Publication Date
- 2026-05-01
AI Technical Summary
Existing technologies lack an immune age assessment scheme that combines good accuracy, strong interpretability, and clinical applicability, especially for low-cost probability prediction of specific disease risks, making it difficult to apply effectively in health management and early intervention.
An immune age prediction model based on multiple linear regression and binary logistic regression was constructed. By screening immune biomarkers that are significantly related to age, such as red blood cell count, TNF-α, absolute CD8+ T cell count and absolute CD4+ T cell count, a risk prediction model for respiratory diseases was established, and risk assessment was carried out in combination with actual age group.
This represents a leap from traditional qualitative assessment to precise probabilistic prediction, providing a low-cost basis for risk stratification and personalized intervention in health management, and improving the accuracy and interpretability of disease risk prediction.