An explainable machine learning platform for pyrazinamide resistance prediction and genetic feature identification of Mycobacterium tuberculosis.

Journal: Journal of the American Medical Informatics Association : JAMIA
PMID: 33215194

Abstract

OBJECTIVE: Tuberculosis is the leading cause of death from a single infectious agent. The emergence of antimicrobial resistant Mycobacterium tuberculosis strains makes the problem more severe. Pyrazinamide (PZA) is an important component for short-course treatment regimens and first- and second-line treatment regimens. This research aims for fast diagnosis of M. tuberculosis resistance to PZA and identification of genetic features causing resistance.

Authors

  • Andrew Zhang
    Amazon Web Service, 450 West 33rd Street, New York, NY 10001, USA.
  • Ling Teng
    Department of Medicine, Brigham and Women's Hospital/Harvard Medical School, Boston, Massachusetts, USA.
  • Gil Alterovitz
    Center for Biomedical Informatics, Harvard Medical School, Boston, USA; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, USA; Children׳s Hospital Informatics Program at the Harvard/MIT Division of Health Sciences and Technology, Boston, USA. Electronic address: gil_alterovitz@hms.harvard.edu.

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