Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/7834
Title: Artificial intelligence as diagnostic modality for keratoconus: A systematic review and meta-analysis
Authors: Afifah, Azzahra
Syafira, Fara
Afladhanti, Putri Mahirah
Dharmawidiarini, Dini
Keywords: Artificial intelligence
Diagnostic modality
Keratoconus
Meta-analysis
Systematic review
Issue Date: 2024
Publisher: Journal of Taibah University Medical Sciences
Series/Report no.: Review Article;296-303
Abstract: Objectives: The challenges in diagnosing keratoconus (KC) have led researchers to explore the use of artificial intelligence (AI) as a diagnostic tool. AI has emerged as a new way to improve the efficiency of KC diagnosis. This study analyzed the use of AI as a diagnostic modality for KC. Methods: This study used a systematic review and metaanalysis following the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched selected databases using a combination of search terms: “((Artificial Intelligence) OR (Diagnostic Modality)) AND (Keratoconus)” from PubMed, Medline, and ScienceDirect within the last 5 years (2018e2023). Following a systematic review protocol, we selected 11 articles and 6 articles were eligible for final analysis. The relevant data were analyzed with Review Manager 5.4 software and the final output was presented in a forest plot. Results: This research found neural networks as the most used AI model in diagnosing KC. Neural networks and naı¨ve bayes showed the highest accuracy of AI in diagnosing KC with a sensitivity of 1.00, while random forests were >0.90. All studies in each group have proven high sensitivity and specificity over 0.90. Conclusions: AI potentially makes a better diagnosis of the KC with its high performance, particularly on sensitivity and specificity, which can help clinicians make medical decisions about an individual patient.
URI: http://localhost:8080/xmlui/handle/123456789/7834
ISSN: 1658-3612
Appears in Collections:Vol 19 No 2 (2024)

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