Using LLMs with decision support could improve diagnoses, MGB shows

Mass General Brigham researchers see value in a hybrid approach that makes use of generative artificial intelligence to diagnose patients.

Comparing two large language models (LLMs) – OpenAI's GPT-4 and Google's Gemini 1.5 – with its homegrown diagnostic decision support system, DXplain, MGB scientists found that the DDSS outperformed the LLMs in accurately diagnosing patient cases – but that the two types of AI could augment one another to better inform treatment.

WHY IT MATTERS

DXplain was first developed in Boston back in 1984 as a standalone platform and has since evolved into a web-based application and cloud-based differential diagnosis engine. It currently relies on 2,680 disease profiles, more than 6,100 clinical findings and hundreds of thousands of data points that generate an