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

• Published in: Computational and structural biotechnology journal Vol. 23; pp. 4019 - 4026
• Main Authors: Gumilar, Khanisyah Erza, Indraprasta, Birama R., Faridzi, Ach Salman, Wibowo, Bagus M., Herlambang, Aditya, Rahestyningtyas, Eccita, Irawan, Budi, Tambunan, Zulkarnain, Bustomi, Ahmad Fadhli, Brahmantara, Bagus Ngurah, Yu, Zih-Ying, Hsu, Yu-Cheng, Pramuditya, Herlangga, Putra, Very Great E., Nugroho, Hari, Mulawardhana, Pungky, Tjokroprawiro, Brahmana A., Hedianto, Tri, Ibrahim, Ibrahim H., Huang, Jingshan, Li, Dongqi, Lu, Chien-Hsing, Yang, Jer-Yen, Liao, Li-Na, Tan, Ming
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.12.2024; Research Network of Computational and Structural Biotechnology; Elsevier
• Subjects: Accuracy; Artificial intelligence; biotechnology; Consistency; decision making; Gynecologic cancer; Large Language Models; patients; Accuracy; Large Language Models; Artificial intelligence; Gynecologic cancer; Consistency

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. LLMs are advancing rapidly and require a thorough evaluation to ensure that they can be safely and effectively used in...