Bridging the Gap in Neonatal Care: Evaluating AI Chatbots for Chronic Neonatal Lung Disease and Home Oxygen Therapy Management.

Journal: Pediatric pulmonology
PMID: 40042139

Abstract

OBJECTIVE: To evaluate the accuracy and comprehensiveness of eight free, publicly available large language model (LLM) chatbots in addressing common questions related to chronic neonatal lung disease (CNLD) and home oxygen therapy (HOT).

Authors

  • Weiqin Liu
    Department of Neonatology, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China.
  • Hong Wei
    Department of Materials Science and Engineering, University of California, Irvine, California 92697, United States.
  • Lingling Xiang
    Department of Neonatology, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China.
  • Yin Liu
    School of Chemistry and Chemical Engineering, Shandong University, Jinan, China.
  • Chunyi Wang
    Department of Social and Human Sciences, Tokyo Institute of Technology, Meguro-ku,Tokyo, Japan.
  • Ziyu Hua
    Department of Neonatology, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China.

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