{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T06:59:46Z","timestamp":1790319586164,"version":"4.1.0"},"reference-count":49,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["APMIS"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Ophthalmic imaging has advanced to a level at which it can closely approximate key histopathological features of certain ocular tissues, changing the way ocular disease is screened for, diagnosed, and monitored. Modalities such as optical coherence tomography (OCT), anterior segment OCT (AS\u2010OCT), OCT angiography (OCTA), and in\u00a0vivo confocal microscopy (IVCM) capture tissue architecture with high\u2010resolution structural and even microvascular information. In this review, the authors summarize the current evidence on artificial intelligence (AI) based applications that utilize high\u2010resolution ophthalmic imaging and digital pathology to support near\u2010histologic interpretation across a range of ocular diseases. Reported diagnostic performance and concordance with histopathologic findings are examined while describing the technical, biological, and regulatory boundaries of AI\u2010derived inference. While AI supports objective, scalable, and reproducible analyses of ophthalmic imaging data, limitations in resolution, generalizability, and specificity prevent its use as an independent substitute for tissue\u2010based diagnosis where histopathologic confirmation is required.<\/jats:p>","DOI":"10.1111\/apm.70253","type":"journal-article","created":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T03:31:35Z","timestamp":1788319895000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Review of the Use of Artificial Intelligence in Ophthalmology Imaging: Approximation to Ocular Histopathology"],"prefix":"10.1111","volume":"134","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8537-8712","authenticated-orcid":false,"given":"Jimena Tatiana","family":"Hathaway","sequence":"first","affiliation":[{"name":"David G. 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