一种用于甲氨蝶呤给药的药方识别匹配方法
By comprehensively analyzing patients' electronic medical records and modeling causal relationships, individualized methotrexate dosing regimens are generated, solving the problem of the lack of individualization in existing methotrexate dosing regimens and achieving more rational and effective dosing regimen recommendations.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- FUJIAN PROVINCIAL HOSPITAL
- Filing Date
- 2026-04-01
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies make it difficult to establish a correlation between changes in patient disease status and drug treatment response using multi-source clinical data in electronic medical records, resulting in a lack of individualized and effective matching methods for methotrexate dosing regimens.
By extracting historical clinical and prescription records from the target patient's electronic medical records, a manifold trajectory of disease activity is generated, drug efficacy decay state parameters are analyzed, and a Gaussian mixture model is used to identify decay subtypes. A causal contribution weight vector is constructed, and dosing regimens for similar patients are retrieved from the historical case database to generate a list of recommended prescriptions.
It enables individualized recommendations for methotrexate dosing regimens, improving the rationality and effectiveness of dosing regimens, and provides a set of candidate intervention trajectories with multiple intervention branches and success probability distributions based on causal relationship analysis.
Smart Images
Figure CN121983230B_ABST