Titlebook: Artificial Intelligence in Ophthalmology; Andrzej Grzybowski Book 2021 Springer Nature Switzerland AG 2021 Automatic software.Deep learnin

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Google and DeepMind: Deep Learning Systems in Ophthalmology,y, artificial intelligence studies have spanned a diverse spectrum including algorithm development, human computer interaction, clinical validation, and novel biomarker discovery. In this chapter we highlight the work of Google and DeepMind in these areas, as a set of end-to-end case studies for dev

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Singapore Eye Lesions Analyzer (SELENA): The Deep Learning System for Retinal Diseases,cular degeneration (AMD), retinopathy of prematurity and systemic cardiovascular diseases. In 2017, an international team of physicians and computer scientists reported that the Singapore Eye Lesion Analyzer (SELENA), a DL system, possessed excellent diagnostic performance for three major blinding c

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Artificial Intelligence for Cataract Management,duce healthcare burdens. However, imbalanced distribution of medical resources has limited the coverage of cataract management. Besides, the current standard of management of cataract patients still needs improvement for better visual outcomes. With the advent of artificial intelligence (AI) technol

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Artificial Intelligence in Cataract Surgery Training,o the reduction of up to 41,846 readmissions and save $620.3 million per year. It has been established that poor technical skill is associated with an increased risk of severe adverse events after surgery, and traditional models to train surgeons are being challenged by rapid advances in technology,

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Artificial Intelligence in Ophthalmology Triaging, are both time consuming and prone to human error. The use of deep learning (DL) and natural language processing (NLP) in ophthalmology triaging is a novel application of artificial intelligence (AI) established at the South Australian Institute of Ophthalmology (SAIO), Australia. AI assisted triagi