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

Journal: Computational and structural biotechnology journal
Published Date: Oct 31, 2024

Abstract

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.

Authors

  • Khanisyah Erza Gumilar
    Graduate Institute of Biomedical Science, China Medical University, Taichung, Taiwan.
  • Birama R Indraprasta
    Department of Obstetrics and Gynecology, Dr. Soetomo General Hospital - Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
  • Ach Salman Faridzi
    Department of Obstetrics and Gynecology, Dr. Soetomo General Hospital - Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
  • Bagus M Wibowo
    Department of Obstetrics and Gynecology, Dr. Soetomo General Hospital - Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
  • Aditya Herlambang
    Department of Obstetrics and Gynecology, Dr. Soetomo General Hospital - Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
  • Eccita Rahestyningtyas
    Department of Obstetrics and Gynecology, Hospital of Universitas Airlangga - Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
  • Budi Irawan
    Department of Obstetrics and Gynecology, Dr. Soetomo General Hospital - Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
  • Zulkarnain Tambunan
    Department of Obstetrics and Gynecology, Dr. Soetomo General Hospital - Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
  • Ahmad Fadhli Bustomi
    Department of Obstetrics and Gynecology, Dr. Soetomo General Hospital - Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
  • Bagus Ngurah Brahmantara
    Department of Obstetrics and Gynecology, Dr. Soetomo General Hospital - Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
  • Zih-Ying Yu
    Department of Public Health, China Medical University, Taichung, Taiwan.
  • Yu-Cheng Hsu
    Department of Public Health, China Medical University, Taichung, Taiwan.
  • Herlangga Pramuditya
    Department of Obstetrics and Gynecology, Dr. Ramelan Naval Hospital, Surabaya, Indonesia.
  • Very Great E Putra
    Department of Obstetrics and Gynecology, Dr. Kariadi Central General Hospital, Semarang, Indonesia.
  • Hari Nugroho
    Department of Obstetrics and Gynecology, Dr. Soetomo General Hospital - Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
  • Pungky Mulawardhana
    Department of Obstetrics and Gynecology, Hospital of Universitas Airlangga - Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
  • Brahmana A Tjokroprawiro
    Department of Obstetrics and Gynecology, Dr. Soetomo General Hospital - Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
  • Tri Hedianto
    Faculty of Medicine and Health, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia.
  • Ibrahim H Ibrahim
    Graduate Institute of Biomedical Science, China Medical University, Taichung, Taiwan.
  • Jingshan Huang
    School of Computing, College of Medicine, University of South Alabama, Mobile, AL, USA.
  • Dongqi Li
    School of Information and Computer Sciences, School of Social and Behavioral Sciences, University of California, Irvine, CA, USA.
  • Chien-Hsing Lu
    Department of Obstetrics and Gynecology, Taichung Veteran General Hospital, Taichung, Taiwan.
  • Jer-Yen Yang
    Graduate Institute of Biomedical Science, China Medical University, Taichung, Taiwan.
  • Li-Na Liao
    Department of Public Health, China Medical University, Taichung, Taiwan.
  • Ming Tan
    Graduate Institute of Biomedical Science, China Medical University, Taichung, Taiwan.

Keywords

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