Integrating landmark modeling framework and machine learning algorithms for dynamic prediction of tuberculosis treatment outcomes.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Apr 13, 2022

Abstract

OBJECTIVE: This study aims to establish an informative dynamic prediction model of treatment outcomes using follow-up records of tuberculosis (TB) patients, which can timely detect cases when the current treatment plan may not be effective.

Authors

  • Maryam Kheirandish
    Department of Industrial Engineering, University of Arkansas, Fayetteville, Arkansas, USA.
  • Donald Catanzaro
    Department of Biological Sciences, University of Arkansas, Fayetteville, Arkansas, USA.
  • Valeriu Crudu
    Institute of Phthisiopneumology "Chrirl Draganiuc," Chisinau, Moldova.
  • Shengfan Zhang
    Department of Industrial Engineering, University of Arkansas, Fayetteville, Arkansas, USA.

Keywords

External Resources

Popular Topics
Recent Journals