[2603.04763] Evaluating GPT-5 as a Multimodal Clinical Reasoner: A Landscape Commentary

Computer Science > Computer Vision and Pattern Recognition arXiv:2603.04763 (cs) [Submitted on 5 Mar 2026] Title:Evaluating GPT-5 as a Multimodal Clinical Reasoner: A Landscape Commentary Authors:Alexandru Florea, Shansong Wang, Mingzhe Hu, Qiang Li, Zach Eidex, Luke del Balzo, Mojtaba Safari, Xiaofeng Yang View a PDF of the paper titled Evaluating GPT-5 as a Multimodal Clinical Reasoner: A Landscape Commentary, by Alexandru Florea and 7 other authors View PDF HTML (experimental) Abstract:The transition from task-specific artificial intelligence toward general-purpose foundation models raises fundamental questions about their capacity to support the integrated reasoning required in clinical medicine, where diagnosis demands synthesis of ambiguous patient narratives, laboratory data, and multimodal imaging. This landscape commentary provides the first controlled, cross-sectional evaluation of the GPT-5 family (GPT-5, GPT-5 Mini, GPT-5 Nano) against its predecessor GPT-4o across a diverse spectrum of clinically grounded tasks, including medical education examinations, text-based reasoning benchmarks, and visual question-answering in neuroradiology, digital pathology, and mammography using a standardized zero-shot chain-of-thought protocol. GPT-5 demonstrated substantial gains in expert-level textual reasoning, with absolute improvements exceeding 25 percentage-points on MedXpertQA. When tasked with multimodal synthesis, GPT-5 effectively leveraged this enhanced reasoning cap...