Automating Colon Polyp Classification in Digital Pathology by Evaluation of a "Machine Learning as a Service" AI Model: Algorithm Development and Validation Study.

Journal: JMIR formative research
Published Date: Jul 31, 2025

Abstract

BACKGROUND: Artificial intelligence (AI) models are increasingly being developed to improve the efficiency of pathological diagnoses. Rapid technological advancements are leading to more widespread availability of AI models that can be used by domain-specific experts (ie, pathologists and medical imaging professionals). This study presents an innovative AI model for the classification of colon polyps, developed using AutoML algorithms that are readily available from cloud-based machine learning platforms. Our aim was to explore if such AutoML algorithms could generate robust machine learning models that are directly applicable to the field of digital pathology.

Authors

  • David Beyer
    Department of Lab Medicine and Pathology, University of Alberta, Edmonton, AB, Canada.
  • Evan Delancey
    Department of Chemistry and Physics, College of Science and Mathematics, Arkansas State University, Jonesboro, AR 72467, United States.
  • Logan McLeod
    Deptartment of Environmental Studies, University of Victoria, Victoria, BC, Canada.

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