Artificial intelligence in the management of ocular diseases: opportunities, challenges, and future directions.
Introduction: Artificial Intelligence (AI), a hallmark of modern computational science, refers to the use of computer algorithms to emulate human intelligence. The field of ophthalmology involves an extensive use of digital imaging and objective datasets; thus, AI can help in early detection of ocul...
| Publicado en: | Expert Review of Ophthalmology Vol. 21; no. 2; pp. 149 - 169 |
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| Autores principales: | , , , |
| Formato: | pictorial review tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Apr2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=192698412&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 192698412 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 17469899 3CML jtl: Expert Review of Ophthalmology issn: 17469899 maglogo: N pubinfo: dt: Apr2026 vid: 21 iid: 2 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 192698412 191884128 192698412 192698412 10.1080/17469899.2026.2633800 192698412 ppf: 149 ppct: 20 formats: tig: atl: Artificial intelligence in the management of ocular diseases: opportunities, challenges, and future directions. aug: au: Sanshita Chaudhari, Kapil Sinha, Lavanya Sinha, V R affil: University Institute of Pharmaceutical Sciences, Panjab University, Chandigarh, India sug: subj: Eye Diseases Diagnosis Eye Diseases Therapy Artificial Intelligence Diagnosis, Computer Assisted Therapy, Computer Assisted Surgery, Computer-Assisted Machine Learning Deep Learning Diabetic Retinopathy Glaucoma Dry Eye Syndromes Uveitis Tomography, Optical Coherence Electrooculography Conjunctivitis Myopia Cataract Eye Diseases Risk Factors Risk Assessment Eye Diseases Surgery Eye Diseases Drug Therapy Drug Delivery Systems ab: Introduction: Artificial Intelligence (AI), a hallmark of modern computational science, refers to the use of computer algorithms to emulate human intelligence. The field of ophthalmology involves an extensive use of digital imaging and objective datasets; thus, AI can help in early detection of ocular diseases like diabetic retinopathy and glaucoma, by processing retinal, fundus, and optical coherence tomography scans with a high level of precision. AI ultimately aids in understanding alterations in nerve health, visual field, cup-to-disc ratio, and retinal vascular parameters. Areas covered: This review provides an updated view of the application of AI in the management of ocular diseases, drawing insights from a plethora of literature and research studies. Additionally, the significant progress made by AI in the domain of drug delivery and ophthalmic surgery has also been explored. The review also addresses the unmet gaps and challenges faced in implementing AI. Expert opinion: Enormous research is still ongoing to maximize AI's versatility across multiple applications. The use of sophisticated machine learning (ML) and deep learning (DL) algorithms has already become an integral part of ophthalmology. This convergence holds revolutionizing capabilities in diagnostic, screening, and even surgical workflows, ultimately allowing clinicians to garner their attention toward patient care. pubtype: Academic Journal doctype: pictorial review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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