cONTACT uS

Research
Automating Glaucoma Diagnosis using Artificial Intelligence
(Original Title: MLCs for Advanced Glaucoma Diagnosis: A Study within the Ghanaian Healthcare Context)
Published on: October 31, 2024 | Dr. Emmanuel Adator
Affiliated Organisation(s): University of Cape Coast,
Research themes
#Innovation, #Product Development, #Artificial intelligence, #Health
Categories
#CSOs, NGOs, etc, #Development partners, #Government institutions, #Industry associations
Abstract

This study focuses on automating the diagnosis of glaucoma, a leading cause of irreversible vision loss, through machine learning classifiers (MLCs). Using data from 605 patients in Ghana, the research integrated Optical Coherence Tomography (OCT) and Visual Field Test (VFT) parameters to predict glaucoma status. Ten machine learning algorithms were tested, with Naïve Bayes achieving the highest diagnostic accuracy (AUROC 0.92). The findings suggest that machine learning can significantly improve diagnostic efficiency and accuracy, particularly in resource-constrained settings.


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  • Council of Scientific and Industrial Research (CSIR)
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  • European Chamber of Commerce
  • Ghana Academy of Arts and Sciences

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