Evaluating an AI Model to Help Doctors Make Medical Decisions Using Real-Time Hospital Data

What this Trial Is About

Researchers are evaluating an artificial intelligence AI model designed to help doctors predict patient diagnoses and outcomes, such as survival and length of hospital stay. This prospective study uses real-time, multimodal health data from hospital electronic health records, including labs, vital signs, medical history, and imaging. The goal is to improve the accuracy and speed of diagnosis and treatment in real-world hospital settings, enhancing patient care. The study involves patients admitted to various hospital departments, including ICU, general wards, emergency, and outpatient services. The AI system integrates multiple types of patient data to support clinical decision-making while patients continue to receive standard examinations and care. This observational study follows patients to compare the AI models performance with standard practice over time. Participants will be tracked using electronic health records and hospital data to assess outcomes such as diagnostic accuracy, hospital resource use, and adverse event rates over one year. Researchers will measure improvements in hospital efficiency, patient outcomes, and population health impact. The study aims to provide real-world evidence of how AI may assist medical decision-making across hospital settings.

AI-Assisted Medical Decision-Making