Evaluating multimodal AI in medical diagnostics

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Abstract: This study evaluates multimodal AI models’ accuracy and responsiveness in answering NEJM Image Challenge questions, juxtaposed with human collective intelligence, underscoring AI’s potential and current limitations in clinical diagnostics. Anthropic’s Claude 3 family demonstrated the highest accuracy among the evaluated AI models, surpassing the average human accuracy, while collective human decision-making outperformed all AI models. GPT-4 Vision Preview exhibited selectivity, responding more to easier questions with smaller images and longer questions

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Notes: npj digital medicine. - 7, 1 (2024) , 205, ISSN: 2398-6352

Classification: Medizin, Gesundheit

Event: Veröffentlichung

(where): Freiburg

(who): Universität

(when): 2024

Creator: Kaczmarczyk, Robert
Wilhelm, Theresa Isabelle
Martin, Ron
Roos, Jonas

DOI: 10.1038/s41746-024-01208-3

URN: urn:nbn:de:bsz:25-freidok-2565754

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:20 AM CEST

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Associated

Kaczmarczyk, Robert
Wilhelm, Theresa Isabelle
Martin, Ron
Roos, Jonas
Universität

Time of origin

2024

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