STM Journals Peer-reviewed research from Consortium e-Learning Network

Research and Reviews: A Journal of Health Professions Review Article

The Integration of Artificial Intelligence in Ophthalmology: Augmenting Clinical Decision or Clinical Dependency?

  1. Sankhajyoti Saha Department of Vision Science, Bhawanipur College of Creative Arts and & Applied Sciences
  2. Moubani Dutta Department of Dietetics and Nutrition, Bhawanipur College of Creative Arts and & Applied Sciences, Kolkata, India

Abstract

The diagnostic accuracy of artificial intelligence (AI) algorithms for glaucoma and diabetic retinopathy screening is on par with or higher than that of skilled doctors. Their acceptance has accelerated due to regulatory clearances, practical implementation in telehealth networks, and growing proof of cost-effectiveness. However, this very success raises a question that the field has been reluctant to address: are we unintentionally undermining the clinical reasoning abilities of the upcoming generation of ophthalmologists as AI systems take over tasks that were once the foundation of ophthalmic training, such as grading fundus photos, interpreting optical coherence tomography, and identifying subtle disc changes? To maintain independent clinical judgment in an AI-augmented era, this viewpoint looks at the growing evidence on automation bias and diagnostic deskilling in medicine, considers how these phenomena may specifically manifest in ophthalmology, and suggests that the field should purposefully redesign residency curricula.

Keywords

References (19)

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