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Elsevier Computational Methods and Deep Learning for Ophthalmology

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Description

Computational Methods and Deep Learning for Ophthalmology provides the essential concepts and methods required to design and implement advanced computer-aided diagnosis systems. Published by Academic Press, this text focuses on using technology to identify ophthalmologic abnormalities in the human eye. Readers will explore various computational approaches, including Deep Convolutional Neural Networks, Generative Adversarial Networks, Auto Encoders, and Recurrent Neural Networks. The book also covers modified and hybrid Artificial Neural Networks to assist in medical assessment. Specific applications discussed include the diagnosis of conditions such as Glaucoma, offering a technical foundation for those working at the intersection of computing and eye health.

Key Features

Learn to design advanced computer-aided diagnosis systems for ophthalmologic abnormalities using Elsevier research.

Explore diverse computational approaches including Deep Convolutional Neural Networks and Generative Adversarial Networks.

Study the application of Auto Encoders and Recurrent Neural Networks for assessing the human eye.

Gain technical knowledge on modified and hybrid Artificial Neural Networks for medical diagnosis.

Review specific computational methods used for detecting ophthalmologic abnormalities like Glaucoma.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
24 February 2023
Listed Since
19 July 2022

Barcode

No barcode data available

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