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Artificial intelligence applications and cataract management: A systematic review

Authors :
Daniele Tognetto
Magdalena Rejdak
Serena Milan
Mario Damiano Toro
Sandrine Zweifel
Rosa Giglio
Katarzyna Załuska-Ogryzek
Alex Lucia Vinciguerra
Robert Rejdak
University of Zurich
Giglio, Rosa
Tognetto, Daniele
Vinciguerra, Alex Lucia
Milan, Serena
Rejdak, Robert
Rejdak, Magdalena
Zaluska-Ogryzek, Katarzyna
Zweifel, Sandrine
Toro, Mario Damiano
Tognetto, D.
Giglio, R.
Vinciguerra, A. L.
Milan, S.
Rejdak, R.
Rejdak, M.
Zaluska-Ogryzek, K.
Zweifel, S.
Toro, M. D.
Source :
Survey of Ophthalmology. 67:817-829
Publication Year :
2022
Publisher :
Elsevier BV, 2022.

Abstract

Artificial intelligence (AI)-based applications exhibit the potential to improve the quality and efficiency of patient care in different fields, including cataract management. A systematic review of the different applications of AI-based software on all aspects of a cataract patient's management, from diagnosis to follow-up, was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. All selected articles were analyzed to assess the level of evidence according to the Oxford Centre for Evidence-Based Medicine 2011 guidelines, and the quality of evidence according to the Grading of Recommendations Assessment, Development and Evaluation system. Of the articles analyzed, 49 met the inclusion criteria. No data synthesis was possible for the heterogeneity of available data and the design of the available studies. The AI-driven diagnosis seemed to be comparable and, in selected cases, to even exceed the accuracy of experienced clinicians in classifying disease, supporting the operating room scheduling, and intraoperative and postoperative management of complications. Considering the heterogeneity of data analyzed, however, further randomized controlled trials to assess the efficacy and safety of AI application in the management of cataract should be highly warranted. (c) 2021 The Authors. Published by Elsevier Inc.

Details

ISSN :
00396257
Volume :
67
Database :
OpenAIRE
Journal :
Survey of Ophthalmology
Accession number :
edsair.doi.dedup.....aa0308864ac521b31c29710f290639bd
Full Text :
https://doi.org/10.1016/j.survophthal.2021.09.004