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

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Artificial Intelligence in Ophthalmology Triaging,1%. Technical challenges in AI assisted triaging include small dataset size, distant labels and the presence of specialized medical vocabulary. Future research relating to AI assisted triaging should endeavour to use larger sample sizes, specialist guided triage allocation, and data from multiple centres.

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Free-Radical

V. M.-Y. Lee,J. Q. Trojanowski,Y. Christenical liability [1]. Autonomous AI systems are thus different from Assistive AI sys-tems, which help a clinician make better diagnos-tic or management decisions, and where the liability for the medical decision remains with the clinician [2].

itinerary

https://doi.org/10.1007/978-3-662-55484-5nd 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 developing and implementing artificial intelligence in clinical practice.

Sciatica

Basics of Artificial Intelligence for Ophthalmologists,t much insight into how these results were accomplished. This chapter intends to comprehensively elucidate the basic principles of Artificial Intelligence to help ophthalmologists get a feel for the strengths and limits of the techniques, as well as how they may use them in clinical practice.

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