{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T21:27:37Z","timestamp":1792790857819,"version":"4.5.0"},"reference-count":262,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T00:00:00Z","timestamp":1755475200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Vision"],"abstract":"<jats:p>We evaluated the clinical applications of artificial intelligence models in diagnosing corneal diseases, highlighting their performance metrics and clinical potential. A systematic search was conducted for several disease categories: keratoconus (KC), Fuch\u2019s endothelial corneal dystrophy (FECD), infectious keratitis (IK), corneal neuropathy, dry eye disease (DED), and conjunctival diseases. Metrics such as sensitivity, specificity, accuracy, and area under the curve (AUC) were extracted. Across the diseases, convolutional neural networks and other deep learning models frequently achieved or exceeded established diagnostic benchmarks (AUC &gt; 0.90; sensitivity\/specificity &gt; 0.85\u20130.90), with a particularly strong performance for KC and FECD when trained on consistent imaging modalities such as anterior segment optical coherence tomography (AS-OCT). Models for IK and conjunctival diseases showed promise but faced challenges in heterogeneous image quality and limited objective training criteria. DED and tear film models benefited from multimodal data yet lacked direct comparisons with expert clinicians. Despite high diagnostic precision, challenges from heterogeneous data, a lack of standardization in disease definitions, imaging acquisition, and model training remain. The broad implementation of artificial intelligence must address these limitations to improve eye care equity.<\/jats:p>","DOI":"10.3390\/vision9030071","type":"journal-article","created":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T15:34:53Z","timestamp":1755531293000},"page":"71","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Clinical Applications of Artificial Intelligence in Corneal Diseases"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7831-0154","authenticated-orcid":false,"given":"Omar","family":"Nusair","sequence":"first","affiliation":[{"name":"Kittner Eye Center, Department of Ophthalmology, University of North Carolina, Chapel Hill, NC 27517, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0744-8337","authenticated-orcid":false,"given":"Hassan","family":"Asadigandomani","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, University of California, San Francisco, CA 94143, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hossein","family":"Farrokhpour","sequence":"additional","affiliation":[{"name":"Translational Ophthalmology Research Center, Farabi Eye Hospital, Tehran University of Medical Sciences, Tehran 1336616351, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fatemeh","family":"Moosaie","sequence":"additional","affiliation":[{"name":"Universal Scientific Education and Research Network (USERN), Tehran University of Medical Sciences, Tehran 1416634793, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zahra","family":"Bibak-Bejandi","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, IL 60612, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4386-4672","authenticated-orcid":false,"given":"Alireza","family":"Razavi","sequence":"additional","affiliation":[{"name":"Eye Research Center, Farabi Eye Hospital, Tehran University of Medical Sciences, Tehran 1336616351, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kimia","family":"Daneshvar","sequence":"additional","affiliation":[{"name":"Eye Research Center, Farabi Eye Hospital, Tehran University of Medical Sciences, Tehran 1336616351, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6546-3546","authenticated-orcid":false,"given":"Mohammad","family":"Soleimani","sequence":"additional","affiliation":[{"name":"Kittner Eye Center, Department of Ophthalmology, University of North Carolina, Chapel Hill, NC 27517, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e144","DOI":"10.1016\/S2214-109X(20)30489-7","article-title":"Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: The Right to Sight: An analysis for the Global Burden of Disease Study","volume":"9","author":"Steinmetz","year":"2021","journal-title":"Lancet Glob. 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