1. Artificial intelligence applications and cataract management: A systematic review
- Author
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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., and Toro, M. D.
- Subjects
10018 Ophthalmology Clinic ,medicine.medical_specialty ,complications ,diagnosis ,media_common.quotation_subject ,complication ,610 Medicine & health ,Cataract ,Postoperative management ,law.invention ,surgery ,cataract management ,Randomized controlled trial ,Artificial Intelligence ,law ,medicine ,artificial intelligence ,intraocular lens calculation ,Humans ,Medical physics ,Quality (business) ,Grading (education) ,media_common ,business.industry ,Evidence-based medicine ,2731 Ophthalmology ,Quality of evidence ,diagnosi ,Ophthalmology ,Systematic review ,Applications of artificial intelligence ,business ,Human - 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.
- Published
- 2022