ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistance

arXiv:2402.13448v1 Announce Type: cross
Abstract: In the emergency department (ED), patients undergo triage and multiple laboratory tests before diagnosis. This process is time-consuming, and causes ED crowding which significantly impacts patient mortality, medical errors, staff burnout, etc. This work proposes (time) cost-effective diagnostic assistance that explores the potential of artificial intelligence (AI) systems in assisting ED clinicians to make time-efficient and accurate diagnoses. Using publicly available patient data, we collaborate with ED clinicians to curate MIMIC-ED-Assist, a benchmark that measures …

arxiv copilot cs.ai cs.cl cs.lg diagnostic emergency language language model reduce type