Diagnostic Decision-Making Variability Between Novice and Expert Optometrists for Glaucoma: Comparative Analysis to Inform AI System Design.

Journal: JMIR medical informatics
PMID: 39879089

Abstract

BACKGROUND: While expert optometrists tend to rely on a deep understanding of the disease and intuitive pattern recognition, those with less experience may depend more on extensive data, comparisons, and external guidance. Understanding these variations is important for developing artificial intelligence (AI) systems that can effectively support optometrists with varying degrees of experience and minimize decision inconsistencies.

Authors

  • Faisal Ghaffar
    Department of Systems Design Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON, Canada.
  • Nadine M Furtado
    School of Optometry and Vision Science, University of Waterloo, Waterloo, ON, Canada.
  • Imad Ali
    Department of Computer Science, University of Swat, Mingora, Pakistan.
  • Catherine Burns
    Department of Systems Design Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON, Canada.

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