Diagnosis and treatment records are usually characterized by profound professional knowledge, rich pathography, and dynamic and complex course of disease. Extracting the key disease information from the massive redundant and complicated disease records, accurately evaluating the health status of patients, and providing the medical evidence based basis are the challenges that must be overcome to achieve efficiency enhancement and empowerment for medical staffs, and comprehensively help graded hospitals solve the problems in medical resource allocation and structure optimization.

iFLYHealth proposes T-MDKG technology, that is, Time-aware Medical Risk Prediction Based on a Dynamic Knowledge Graph. Through the whole-course progressive contextual time-aware analysis of patients' pathography at different stages, it realizes real-time prognosis for the progression of the disease, significantly enhances the efficiency of the physician evaluation, and improves medical quality and safety.