Development of a Machine learning image segmentation-based algorithm for the determination of the adequacy of Gram-stained sputum smear images.

Journal: Medical journal, Armed Forces India
Published Date: Nov 28, 2021

Abstract

BACKGROUND: Machine learning (ML) prepares and trains a model through supervised or unsupervised learning methods. Sputum, a respiratory tract secretion, is a common laboratory specimen that aids in diagnosing respiratory diseases, including pulmonary tuberculosis (TB). Gram stain is an easy, cost-effective stain, which may be applied to sputum smears to screen out an unsatisfactory sample. ML model may help in screening sputum smears.

Authors

  • Manraj Sirohi
    Medical Cadet, Armed Forces Medical College, Pune, India.
  • Mahima Lall
    Professor, Department of Microbiology, Armed Forces Medical College, Pune, India.
  • Swapna Yenishetti
    Applied Artificial Intelligence Group, Center for Development of Advanced Computing, Pune, India.
  • Lakshmi Panat
    Applied Artificial Intelligence Group, Center for Development of Advanced Computing, Pune, India.
  • Ajai Kumar
    Applied Artificial Intelligence Group, Center for Development of Advanced Computing, Pune, India.

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