Disease prediction analysis method based on multi-modal medical data
By constructing modally weighted organ topology maps and performing quantum entanglement graph analysis, the problem of insufficient lesion region localization in multimodal medical data modeling was solved, thereby improving the accuracy and foresight of disease prediction.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NANJING KAIDE MEDICAL TECHNOLOGY CO LTD
- Filing Date
- 2025-05-30
- Publication Date
- 2026-06-12
AI Technical Summary
Existing multimodal medical data modeling is difficult to effectively capture complementary information between different modalities in disease prediction, cannot accurately locate potential lesion areas, and traditional methods are insufficient in modeling disease spread paths, making it difficult to meet the needs of refined medical prediction.
By constructing a modality-weighted organ topology map, using quantum graph calculations to simulate the spread of disease characteristics, and combining power-law propagation and quantum entanglement graph analysis, suspected spread lesion areas are extracted and predicted.
It enables deep correlation analysis of multimodal medical data, improves the accuracy and foresight of disease prediction, better reveals high-order correlations in lesion areas, and enhances the temporal continuity and robustness of prediction results.
Smart Images
Figure CN120636794B_ABST