The system also built an intelligent medical insurance review and management platform called "Brain" based on full medical records, which uses AI to review prescriptions, solve problems such as medication exceeding medical insurance payment standards, and conduct in-process control of medical insurance funds.
Is AI auditing reliable? Nie Guangmeng introduced that the system uses clinical medical record semantic understanding and medical knowledge graph technology, and successfully passed the "National Clinical Practitioner Qualification Examination Comprehensive Written Test" with a score of 456, exceeding 96% of human candidates. At present, it has formed 2 million medical knowledge graphs, supporting semantic understanding of 14 chapters of inpatient course records and recognition and analysis of more than 100 types of medical professional terms.
In addition, the system conducts post analysis through big data supervision, and constructs an intelligent and closed-loop management network for the entire process of hospital medical insurance fund supervision, achieving comprehensive and real-time monitoring of the usage trajectory of medical insurance funds, making all links traceable, and weaving a full chain fund security prevention and control network of pre prevention and control, in-process control, and post monitoring.
The "Reference Guide for Artificial Intelligence Application Scenarios in the Health Industry" introduces 84 AI+medical application scenarios, and the above cases are just a microcosm of them. One leaf knows autumn, and the wave of innovation in AI healthcare is sweeping in. As for how to better integrate AI with medical needs, it is the next practical and thoughtful proposition, "said Zhou Yi.
