Application of ChatGPT-based artificial intelligence in the diagnosis and management of polycystic ovary syndrome.

Journal: BMC medical informatics and decision making
Published Date:

Abstract

This study systematically develops and evaluates the application value of the PCOS-GPT system, an artificial intelligence (AI) assistant based on ChatGPT technology, in the diagnosis and management of polycystic ovary syndrome (PCOS). The research explores innovative pathways for AI-enabled PCOS diagnosis and treatment, aiming to provide an adjunctive diagnostic tool for standardized clinical decision support. Methods: An evidence-based PCOS knowledge base was constructed, covering dimensions such as epidemiology, etiology, clinical manifestations, diagnosis, treatment, and prognosis. The PCOS-GPT system was developed using GPT-3.5 pretraining combined with fine-tuning on domain-specific datasets. Using data from 85 patients, the diagnostic and therapeutic performance of PCOS-GPT was evaluated multidimensionally-accuracy, readability, and operability-using diagnoses by three expert physicians as the gold standard. Compared with GPT-4, PCOS-GPT demonstrated advantages in diagnostic accuracy for PCOS (95.63% vs. 96.40%). Conclusion: PCOS-GPT is an intelligent diagnostic and therapeutic support tool with advantages in diagnostic accuracy. It holds promise for improving standardization in diagnosis and treatment, empowering patient self-management, enhancing access to high-quality healthcare resources, and offering comprehensive health management for PCOS patients. This innovation promotes the development of smart healthcare, benefiting women's health.

Authors

  • Yingchun Zhu
    Center for Reproductive Medicine and Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
  • Danchen Luo
    School of Economics and Management, South China Normal University, Guangzhou, China.
  • Xiaoyue Shen
    Center for Reproductive Medicine and Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
  • Qingqing Shi
    Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China.
  • Haining Lv
    Center for Reproductive Medicine and Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
  • Simin Zhang
    Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.
  • Feihong Ye
    School of Chemistry, South China Normal University, Guangzhou, China.
  • Na Kong
    Nanjing Drum Tower Hospital, Drum Tower Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, 210008, Jiangsu, China.