10월 17, 2022 | Asia-Pacific Journal of Ophthalmology
Asia-Pacific Journal of Ophthalmology, May 2021 Artificial Intelligence (AI), in particular deep learning, has made waves in the health care industry, with several prominent examples shown in ophthalmology. Despite the burgeoning reports on the development of new AI...10월 17, 2022 | British Journal of Ophthalmology
British Journal of Ophthalmology, April 2021 Background To develop computer-aided detection (CADe) of ORL abnormalities in the retinal pigmented epithelium, interdigitation zone, and ellipsoid zone via optical coherence tomography (OCT). Methods In this retrospective...10월 17, 2022 | THE LANCET Digital Health
THE LANCET Digital Health, October 2020 Background The application of deep learning to retinal photographs has yielded promising results in predicting age, sex, blood pressure, and hematological parameters. However, the broader applicability of retinal...10월 17, 2022 | British Journal of Ophthalmology
British Journal of Ophthalmology, September 2020 Background The ability of deep learning (DL) algorithms to identify eyes with neovascular age-related macular degeneration (nAMD) from optical coherence tomography (OCT) scans has been previously established. We...10월 17, 2022 | Ophthalmology Retina
Ophthalmology Retina, August 2020 Purpose Though the domain of big data and artificial intelligence in health care continues to evolve, there is a lack of systemic methods to improve data quality and streamline the preparation process. To address this, we aimed to...10월 24, 2022 | ARVO Annual Meeting Abstract
ARVO Annual Meeting Abstract, June 2020 Purpose There is increasing research using deep learning (DL) algorithms for detection of major retinal diseases such as diabetic retinopathy from color fundus photographs (CFP). Because eye diseases vary substantially by...