Visual-textual integration in LLMs for medical diagnosis: A preliminary quantitative analysis

Background and aim: Visual data from images is essential for many medical diagnoses. This study evaluates the performance of multimodal Large Language Models (LLMs) in integrating textual and visual information for diagnostic purposes. Methods: We tested GPT-4o and Claude Sonnet 3.5 on 120 clinical...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής

Κύριοι συγγραφείς:	Reem Agbareia, Mahmud Omar, Shelly Soffer, Benjamin S. Glicksberg, Girish N. Nadkarni, Eyal Klang
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	Elsevier 2025-01-01
Σειρά:	Computational and Structural Biotechnology Journal
Θέματα:	Artificial intelligence Medical diagnosis Multimodal learning Large language models Visual data integration
Διαθέσιμο Online:	http://www.sciencedirect.com/science/article/pii/S2001037024004379
Ετικέτες:	Προσθήκη ετικέτας Δεν υπάρχουν, Καταχωρήστε ετικέτα πρώτοι!