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Assessment of Large Language Models (LLMs) in decision-making support for gynecologic oncology

Objective: This study investigated the ability of Large Language Models (LLMs) to provide accurate and consistent answers by focusing on their performance in complex gynecologic cancer cases. Background: LLMs are advancing rapidly and require a thorough evaluation to ensure that they can be safely a...

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Principais autores: Khanisyah Erza Gumilar, Birama R. Indraprasta, Ach Salman Faridzi, Bagus M. Wibowo, Aditya Herlambang, Eccita Rahestyningtyas, Budi Irawan, Zulkarnain Tambunan, Ahmad Fadhli Bustomi, Bagus Ngurah Brahmantara, Zih-Ying Yu, Yu-Cheng Hsu, Herlangga Pramuditya, Very Great E. Putra, Hari Nugroho, Pungky Mulawardhana, Brahmana A. Tjokroprawiro, Tri Hedianto, Ibrahim H. Ibrahim, Jingshan Huang, Dongqi Li, Chien-Hsing Lu, Jer-Yen Yang, Li-Na Liao, Ming Tan
Formato: Artigo
Idioma:Inglês
Publicado em: Elsevier 2024-12-01
coleção:Computational and Structural Biotechnology Journal
Assuntos:
Gynecologic cancer
Large Language Models
Accuracy
Consistency
Artificial intelligence
Acesso em linha:http://www.sciencedirect.com/science/article/pii/S2001037024003702
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