{"title":"十年后:人工智能如何影响今天的视网膜护理?","authors":"David Kuo, Miroslav Pajic, Majda Hadziahmetovic","doi":"10.1097/ICU.0000000000001167","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose of review: </strong>Artificial intelligence (AI) is transforming retina care, with deep learning (DL) models shaping a new era of improved screening accessibility, diagnostic precision, and personalized disease monitoring. This review highlights recent AI-powered clinical applications in diabetic retinopathy (DR), and age-related macular degeneration (AMD) care.</p><p><strong>Recent findings: </strong>Since the FDA's authorization of the first autonomous AI system for DR screening in 2018, multiple platforms have emerged, expanding access to diabetic eye care. Real-world studies have confirmed a significant improvement in screening adherence and diagnostic accuracy, illustrating AI's tangible impact on public health. Meanwhile, newly certified AI technologies that meet European regulatory standards are increasingly guiding clinical decision-making in the management of AMD and diabetic macular edema through automated analysis of optical coherence tomography (OCT) images. Most recently, FDA-authorized home OCT platforms are transforming AMD monitoring, enabling proactive and remote management of retinal fluid.</p><p><strong>Summary: </strong>As AI increasingly empowers patients and providers, its widespread success still depends on ongoing work, including thorough validation, outcome-based metrics, and improved workflow integration. The next decade will reveal whether AI in retina care transitions from a promising innovation to an essential and indispensable tool in modern retina.</p>","PeriodicalId":50604,"journal":{"name":"Current Opinion in Ophthalmology","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ten years later: how is AI impacting retina care today?\",\"authors\":\"David Kuo, Miroslav Pajic, Majda Hadziahmetovic\",\"doi\":\"10.1097/ICU.0000000000001167\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose of review: </strong>Artificial intelligence (AI) is transforming retina care, with deep learning (DL) models shaping a new era of improved screening accessibility, diagnostic precision, and personalized disease monitoring. This review highlights recent AI-powered clinical applications in diabetic retinopathy (DR), and age-related macular degeneration (AMD) care.</p><p><strong>Recent findings: </strong>Since the FDA's authorization of the first autonomous AI system for DR screening in 2018, multiple platforms have emerged, expanding access to diabetic eye care. Real-world studies have confirmed a significant improvement in screening adherence and diagnostic accuracy, illustrating AI's tangible impact on public health. Meanwhile, newly certified AI technologies that meet European regulatory standards are increasingly guiding clinical decision-making in the management of AMD and diabetic macular edema through automated analysis of optical coherence tomography (OCT) images. Most recently, FDA-authorized home OCT platforms are transforming AMD monitoring, enabling proactive and remote management of retinal fluid.</p><p><strong>Summary: </strong>As AI increasingly empowers patients and providers, its widespread success still depends on ongoing work, including thorough validation, outcome-based metrics, and improved workflow integration. The next decade will reveal whether AI in retina care transitions from a promising innovation to an essential and indispensable tool in modern retina.</p>\",\"PeriodicalId\":50604,\"journal\":{\"name\":\"Current Opinion in Ophthalmology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Opinion in Ophthalmology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/ICU.0000000000001167\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OPHTHALMOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Ophthalmology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/ICU.0000000000001167","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPHTHALMOLOGY","Score":null,"Total":0}
Ten years later: how is AI impacting retina care today?
Purpose of review: Artificial intelligence (AI) is transforming retina care, with deep learning (DL) models shaping a new era of improved screening accessibility, diagnostic precision, and personalized disease monitoring. This review highlights recent AI-powered clinical applications in diabetic retinopathy (DR), and age-related macular degeneration (AMD) care.
Recent findings: Since the FDA's authorization of the first autonomous AI system for DR screening in 2018, multiple platforms have emerged, expanding access to diabetic eye care. Real-world studies have confirmed a significant improvement in screening adherence and diagnostic accuracy, illustrating AI's tangible impact on public health. Meanwhile, newly certified AI technologies that meet European regulatory standards are increasingly guiding clinical decision-making in the management of AMD and diabetic macular edema through automated analysis of optical coherence tomography (OCT) images. Most recently, FDA-authorized home OCT platforms are transforming AMD monitoring, enabling proactive and remote management of retinal fluid.
Summary: As AI increasingly empowers patients and providers, its widespread success still depends on ongoing work, including thorough validation, outcome-based metrics, and improved workflow integration. The next decade will reveal whether AI in retina care transitions from a promising innovation to an essential and indispensable tool in modern retina.
期刊介绍:
Current Opinion in Ophthalmology is an indispensable resource featuring key up-to-date and important advances in the field from around the world. With renowned guest editors for each section, every bimonthly issue of Current Opinion in Ophthalmology delivers a fresh insight into topics such as glaucoma, refractive surgery and corneal and external disorders. With ten sections in total, the journal provides a convenient and thorough review of the field and will be of interest to researchers, clinicians and other healthcare professionals alike.