Development and Validation of a Machine Learning-Based Early Warning Model for Lichenoid Vulvar Disease: Prediction Model Development Study.

Journal: Journal of medical Internet research
Published Date: Nov 22, 2024

Abstract

BACKGROUND: Given the complexity and diversity of lichenoid vulvar disease (LVD) risk factors, it is crucial to actively explore these factors and construct personalized warning models using relevant clinical variables to assess disease risk in patients. Yet, to date, there has been insufficient research, both nationwide and internationally, on risk factors and warning models for LVD. In light of these gaps, this study represents the first systematic exploration of the risk factors associated with LVD.

Authors

  • Jian Meng
    Department of Obstetrics and Gynecology, West China Second Hospital, Sichuan University, Chengdu, China.
  • Xiaoyu Niu
    Department of Gynecology and Obstetrics, West China Second Hospital, Sichuan University, Chengdu, Sichuan, 610041, China. Electronic address: niuxy@scu.edu.cn.
  • Can Luo
    Department of Emergency, Affiliated Hospital of Zunyi Medical University Zunyi, Guizhou, 563003, People's Republic of China.
  • Yueyue Chen
    Department of Obstetrics and Gynecology, West China Second Hospital, Sichuan University, Chengdu, China.
  • Qiao Li
    Department of Biomedical Informatics, Emory University, Atlanta, GA, United States of America.
  • Dongmei Wei
    Department of Obstetrics and Gynecology, West China Second Hospital, Sichuan University, Chengdu, China.

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