https://www.science.org/doi/10.1126/science.aeh7930 “AI applications for clinical medicine continue to advance but often rely on written vignettes. Unfortunately, these are not a realistic representation of clinical medicine, where patients do not come in with a tidy write-up of key symptoms and pertinent laboratory findings. To address this issue, Nori et al. made their AI system start from the patient’s chief complaint and decide what follow-up questions to ask and what testing to order to collect the information needed for a diagnosis. In multiple test settings, this system achieved higher accuracy than human responders and at a lower total cost, demonstrating its potential as a tool to assist physicians. —Yevgeniya Nusinovich “ “We explored the capabilities of frontier language models in sequential diagnosis, a diagnostic paradigm that captures the iterative nature of clinical reasoning. Given a brief clinical presentation, clinicians selectively acquired information to reach a diagnosis, enabling assessment of diagnostic accuracy and workup cost. We developed an interactive benchmark and an artificial intelligence (AI) system that simulates a panel of physicians, continually revising the differential diagnosis and selecting cost-effective tests. Using this benchmark, the system achieved 83.2% accuracy on New England Journal of Medicine clinicopathological conference cases and 80.3% on MIMIC-IV-ED emergency department admissions, outperforming generalist physicians (36.1 and 46.8%, respectively). Although these findings were obtained in a controlled benchmark setting, they highlight the promise of language models for supporting more accurate, lower-cost diagnoses.” Although not the first sequential study, it is the first that chooses diagnostics tests, receives results sequentially, decides when enough evidence exists, evaluates diagnostic costs, and challenges the diagnoses, all with complex cases. Note: All models used are at least 1 year old. MAI-DxO is orchestrator.   submitted by   /u/pstbo [link]   [comments]