A Ophthalmology Study on Eye Glaucoma and Retina Applied in AI and Deep Learning Techniques

Abstract Artificial intelligence based on deep learning has huge global interest in current times. Deep Learning has been widely affiliated in image and speech recognition and also natural language processing, but it is beginning of healthcare. In ophthalmology, Deep learning has applied in photogra...

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Bibliographic Details
Published inJournal of physics. Conference series Vol. 1947; no. 1; pp. 12053 - 12059
Main Authors Vaishnavi, S., Deepa, R., Nanda kumar, P.
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.06.2021
Subjects
Age related diseases
Algorithms
Artificial intelligence
Artificial intelligence (AI)
Deep learning
Diabetic retinopathy
Eye diseases
Glaucoma
Health care
Legal issues
Machine learning
Natural language processing
Object recognition
Ophthalmology
Speech recognition
Telemedicine
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Summary:Abstract Artificial intelligence based on deep learning has huge global interest in current times. Deep Learning has been widely affiliated in image and speech recognition and also natural language processing, but it is beginning of healthcare. In ophthalmology, Deep learning has applied in photographs fundus, optical coherence tomography and vision sectors. Accomplishes safety in classifying the detection performance on diabetic retinopathy, age-related macular degeneration. Deep learning may be used in concurrence with telemedicine as possible to diagnose and monitor major eye diseases for patients in primary care. There are also prospective challenges with Deep learning application in ophthalmology, including clinical and technical challenges, explain ability of the algorithm results, medico legal issues, and physician and patient acceptance of the AI “black-box” algorithms. Deep learning could probably revolutionize how ophthalmology is practiced in the future. Hence this reviewprovides a Deep Learning systems described for ophthalmic conditions, and fundamental functions.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1947/1/012053