Development and validation of a web-based calculator for determining the risk of psychological distress based on machine learning algorithms: A cross-sectional study of 342 lung cancer patients.

Journal: Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PMID: 39738685

Abstract

PURPOSE: Early and accurate identification of the risk of psychological distress allows for timely intervention and improved prognosis. Current methods for predicting psychological distress among lung cancer patients using readily available data are limited. This study aimed to develop a robust machine learning (ML) model for determining the risk of psychological distress among lung cancer patients.

Authors

  • Xu Tian
    Department of Otorhinolaryngology Head and Neck Surgery, the Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Haoyang Li
  • Feili Li
    College of Environment, Zhejiang University of Technology, Hangzhou 310032, China.
  • María F Jiménez-Herrera
    Nursing Department, Universitat Rovira I Virgili, 43002, Tarragona, Spain.
  • Yi Ren
    Institute for Advanced Study, Shenzhen University, Shenzhen, 518060, P. R. China.
  • Hongcai Shang
    Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine, Beijing, China.

Keywords

External Resources

Popular Topics
Recent Journals