In response to the pressing need for advanced clinical problem-solving tools in healthcare, we introduce BooksMed, a novel framework based on a Large Language Model (LLM). BooksMed uniquely emulates human cognitive processes to deliver evidence-based and reliable responses, utilizing the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework to effectively quantify evidence strength. For clinical decision-making to be appropriately assessed, an evaluation metric that is clinically aligned and validated is required. As a solution, we present ExpertMedQA, a multispecialty clinical benchmark comprised of open-ended, expert-level clinical questions, and validated by a diverse group of medical professionals. By demanding an in-depth understanding and critical appraisal of up-to-date clinical literature, ExpertMedQA rigorously evaluates LLM performance. BooksMed outperforms existing state-of-the-art models Med-PaLM 2, Almanac, and ChatGPT in a variety of medical scenarios. Therefore, a framework that mimics human cognitive stages could be a useful tool for providing reliable and evidence-based responses to clinical inquiries.

Kawasaki disease (or mucocutaneous lymph node syndrome) is a disease where blood vessels throughout the body become inflamed. This is manifest through a five-day fever, enlargement of the lymph nodes, a rashes and sometimes diarrhea. The disease is primarily one of children and treatment is usually based on pain killers and the infusion of immunoglobulin. The disease has been known about since World War II (and described in 1967 by Tomisaku Kawasaki in Japan). Despite the passing of time, the cause is still unknown.