The potential application of artificial intelligence for diagnosis and management of glaucoma in adults

Abstract

Background: Glaucoma is the most frequent cause of irreversible blindness worldwide. There is no cure, but early detection and treatment can slow the progression and prevent loss of vision. It has been suggested that artificial intelligence (AI) has potential application for detection and management of glaucoma.

Sources of data: This literature review is based on articles published in peer-reviewed journals.

Areas of agreement: There have been significant advances in both AI and imaging techniques that are able to identify the early signs of glaucomatous damage. Machine and deep learning algorithms show capabilities equivalent to human experts, if not superior.

Areas of controversy: Concerns that the increased reliance on AI may lead to deskilling of clinicians.

Growing points: AI has potential to be used in virtual review clinics, telemedicine and as a training tool for junior doctors. Unsupervised AI techniques offer the potential of uncovering currently unrecognized patterns of disease. If this promise is fulfilled, AI may then be of use in challenging cases or where a second opinion is desirable.

Areas timely for developing research: There is a need to determine the external validity of deep learning algorithms and to better understand how the 'black box' paradigm reaches results.

Keywords: artificial intelligence; deep learning; glaucoma; machine learning; machine learning classifiers; ‘black box’ algorithm.