Automatic Construction of Clinical Scoring Systems with LLM Agents
Researchers have developed AgentScore, a novel method for automatically constructing clinical scoring systems using LLM agents. This approach addresses the challenge of creating interpretable and deployable clinical guidelines by leveraging LLMs to propose rules and a verification loop to ensure statistical validity. AgentScore demonstrated superior performance compared to existing methods across eight clinical prediction tasks and outperformed established scores on two external validation tasks. AI
IMPACT Automates the creation of interpretable clinical scoring systems, potentially improving guideline deployment and patient care.