AgentMD: Empowering Language Agents for Risk Prediction with Large-Scale Clinical Tool Learning

arXiv:2402.13225v1 Announce Type: new
Abstract: Clinical calculators play a vital role in healthcare by offering accurate evidence-based predictions for various purposes such as prognosis. Nevertheless, their widespread utilization is frequently hindered by usability challenges, poor dissemination, and restricted functionality. Augmenting large language models with extensive collections of clinical calculators presents an opportunity to overcome these obstacles and improve workflow efficiency, but the scalability of the manual curation process poses a significant challenge. In response, we introduce AgentMD, a novel language …

abstract agents arxiv challenges clinical cs.ai cs.cl evidence healthcare language language models large language large language models prediction predictions risk role scale tool type usability vital