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Deep learning for cancer diagnosis

Kose, Utku.

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Deep learning for cancer diagnosis

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learning for cancer diagnosis/ edited by Utku Kose, Jafar Alzubi.
other author:	Kose, Utku.
Published:	Singapore :Springer Singapore : : 2021.,
Description:	xix, 300 p. :ill., digital ;24 cm.
[NT 15003449]:	Deep Learning for Enhancing Cancer Diagnosis -- Improved Deep Learning Techniques for Better Cancer Diagnosis -- Deep Learning for Diagnosing Rare Cancer Types -- Deep Learning for Histopathological Diagnosis -- Effective Use of Deep Learning and Image Processing for Cancer Diagnosis.
Contained By:	Springer Nature eBook
Subject:	Cancer - Diagnosis -
Online resource:	https://doi.org/10.1007/978-981-15-6321-8
ISBN:	9789811563218

Deep learning for cancer diagnosis
Deep learning for cancer diagnosis[electronic resource] /edited by Utku Kose, Jafar Alzubi. - Singapore :Springer Singapore :2021. - xix, 300 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.9081860-949X ;. - Studies in computational intelligence ;v.908..

Deep Learning for Enhancing Cancer Diagnosis -- Improved Deep Learning Techniques for Better Cancer Diagnosis -- Deep Learning for Diagnosing Rare Cancer Types -- Deep Learning for Histopathological Diagnosis -- Effective Use of Deep Learning and Image Processing for Cancer Diagnosis.

This book explores various applications of deep learning to the diagnosis of cancer,while also outlining the future face of deep learning-assisted cancer diagnostics. As is commonly known, artificial intelligence has paved the way for countless new solutions in the field of medicine. In this context, deep learning is a recent and remarkable sub-field, which can effectively cope with huge amounts of data and deliver more accurate results. As a vital research area, medical diagnosis is among those in which deep learning-oriented solutions are often employed. Accordingly, the objective of this book is to highlight recent advanced applications of deep learning for diagnosing different types of cancer. The target audience includes scientists, experts, MSc and PhD students, postdocs, and anyone interested in the subjects discussed. The book can be used as a reference work to support courses on artificial intelligence, medical and biomedicaleducation.

ISBN: 9789811563218

Standard No.: 10.1007/978-981-15-6321-8doiSubjects--Topical Terms:

3486429
Cancer
--Diagnosis

LC Class. No.: RC270 / .D44 2021

Dewey Class. No.: 616.994075

Deep learning for cancer diagnosis
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245 0 0 $a Deep learning for cancer diagnosis $h [electronic resource] / $c edited by Utku Kose, Jafar Alzubi.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2021.
300 $a xix, 300 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.908
505 0 $a Deep Learning for Enhancing Cancer Diagnosis -- Improved Deep Learning Techniques for Better Cancer Diagnosis -- Deep Learning for Diagnosing Rare Cancer Types -- Deep Learning for Histopathological Diagnosis -- Effective Use of Deep Learning and Image Processing for Cancer Diagnosis.
520 $a This book explores various applications of deep learning to the diagnosis of cancer,while also outlining the future face of deep learning-assisted cancer diagnostics. As is commonly known, artificial intelligence has paved the way for countless new solutions in the field of medicine. In this context, deep learning is a recent and remarkable sub-field, which can effectively cope with huge amounts of data and deliver more accurate results. As a vital research area, medical diagnosis is among those in which deep learning-oriented solutions are often employed. Accordingly, the objective of this book is to highlight recent advanced applications of deep learning for diagnosing different types of cancer. The target audience includes scientists, experts, MSc and PhD students, postdocs, and anyone interested in the subjects discussed. The book can be used as a reference work to support courses on artificial intelligence, medical and biomedicaleducation.
650 0 $a Cancer $x Diagnosis $x Data processing. $3 3486429
650 0 $a Machine learning. $3 533906
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Machine Learning. $3 3382522
650 2 4 $a Cancer Research. $3 891172
650 2 4 $a Health Informatics. $3 892928
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
650 2 4 $a Signal, Image and Speech Processing. $3 891073
700 1 $a Kose, Utku. $3 3486174
700 1 $a Alzubi, Jafar. $3 3486427
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Studies in computational intelligence ; $v v.908. $3 3486428
856 4 0 $u https://doi.org/10.1007/978-981-15-6321-8
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)