6 stories tagged Clinical
Researchers present a clinician-grounded evaluation platform for AI-assisted psychiatric intake systems, using a memory-augmented patient simulator to support comparison across interviewing approaches, minimize clinician burden, and measure clinically relevant performance.
Researchers developed GuideSkill, an AI system that translates clinical practice guidelines into executable functions to improve diagnostic accuracy. The system can refine its skills over time using real case data, offering a more precise approach to medical decision-making.
Researchers developed a method to predict when AI assistants in healthcare might fail. This could make clinical AI tools safer and more reliable for doctors and patients. The study analyzed real-world use of AI in electronic health records to identify risky responses before they happen.
Researchers found that AI models often fail to handle rare medical cases not covered by standard guidelines. This highlights a critical gap in how medical AI is trained and evaluated.
Researchers propose new ways to test AI models in healthcare to ensure they're safe and reliable. This could make AI tools more trustworthy for doctors and patients.
A new survey and benchmark reveal that while large language models excel at medical exams, their clinical reasoning falls short. The study underscores the need for robust medical reasoning capabilities in real-world healthcare settings.