An AI multi-modal fusion-based gynecological microecological detection system
The gynecological microecology detection system, which integrates AI and multimodal fusion, combines multiple detection methods to construct dynamic models and three-dimensional maps. This overcomes the limitations of single detection methods, enables accurate assessment and dynamic analysis of the gynecological microecology, and improves the accuracy of detection and the efficiency of clinical decision-making.
Patent Information
- Application Number
- CN202511516890.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-23
- Publication Date
- 2026-05-19
- Estimated Expiration
- 2045-10-23
AI Technical Summary
Existing gynecological microecological testing methods rely on single technical means, which cannot comprehensively and accurately reflect the state of vaginal microecology. The data dimensions are limited, the units of measurement are inconsistent, static assessment lacks dynamic analysis, and visualization is insufficient, which affects the efficiency of clinical decision-making.
An AI multimodal fusion detection system was adopted, which combines immunofluorescence signals, Gram staining morphological features and dry chemical indicators. Data was unified through standardized modules, a dynamic model of microbial community parameters was constructed, a three-dimensional microecological map was generated, and pattern recognition and classification were performed through deep learning algorithms.
It enables precise assessment and dynamic analysis of the gynecological microecology, improves the accuracy of identifying mixed infections and early lesions, provides targeted treatment plans and prognostic assessments, and enhances the accuracy and efficiency of clinical diagnosis and treatment.