By using structured clinical data, and semantic understanding of medical records, and relying on the authoritative medical knowledge base, AI-assisted Clinical Assistant deeply integrates the data system of medical institutions and forms three systems, namely clinical aid decision-making support, VTE prevention and treatment, and scientific research platform, and seamlessly empowers assisting diagnosis and treatment, doctor's advice review, VTE smart prevention and treatment, DRG-assisted diagnosis, medical research data integration and other functions in the outpatient and inpatient treatment scenarios, comprehensively improving the work efficiency of medical staff and medical quality.

Intelligent evaluation of “Al+VTE” under the doctor-nurse collaboration mode. Relying on natural language processing and the VTE disease knowledge graph, the VTE prevention and treatment system builds an intelligent evaluation model of VTE risks by seamlessly embedding it with the hospital business system. System AI recommends a high-risk recall rate of 90%, and automatically identifies the thrombosis risk factors of hospitalized patients and their changes, with a consistency rate of AI recommendation grade of 92%.(Quoted from internal test data)