Language:
English
繁體中文
Help
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Deep Learning for Cancer Diagnosis
~
Kose, Utku.
Deep Learning for Cancer Diagnosis
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Deep Learning for Cancer Diagnosis/ edited by Utku Kose, Jafar Alzubi.
other author:
Kose, Utku.
Description:
XIX, 300 p. 118 illus., 87 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Computational intelligence. -
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. - 1st ed. 2021. - XIX, 300 p. 118 illus., 87 illus. in color.online resource. - Studies in Computational Intelligence,9081860-9503 ;. - Studies in Computational Intelligence,564.
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:
568984
Computational intelligence.
LC Class. No.: Q342
Dewey Class. No.: 006.3
Deep Learning for Cancer Diagnosis
LDR
:02682nam a22004095i 4500
001
1049244
003
DE-He213
005
20210914131450.0
007
cr nn 008mamaa
008
220103s2021 si | s |||| 0|eng d
020
$a
9789811563218
$9
978-981-15-6321-8
024
7
$a
10.1007/978-981-15-6321-8
$2
doi
035
$a
978-981-15-6321-8
050
4
$a
Q342
072
7
$a
UYQ
$2
bicssc
072
7
$a
TEC009000
$2
bisacsh
072
7
$a
UYQ
$2
thema
082
0 4
$a
006.3
$2
23
245
1 0
$a
Deep Learning for Cancer Diagnosis
$h
[electronic resource] /
$c
edited by Utku Kose, Jafar Alzubi.
250
$a
1st ed. 2021.
264
1
$a
Singapore :
$b
Springer Singapore :
$b
Imprint: Springer,
$c
2021.
300
$a
XIX, 300 p. 118 illus., 87 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
490
1
$a
Studies in Computational Intelligence,
$x
1860-9503 ;
$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
Computational intelligence.
$3
568984
650
0
$a
Machine learning.
$3
561253
650
0
$a
Cancer research.
$3
1253664
650
0
$a
Health informatics.
$3
1064466
650
0
$a
Optical data processing.
$3
639187
650
0
$a
Signal processing.
$3
561459
650
0
$a
Image processing.
$3
557495
650
0
$a
Speech processing systems.
$3
564428
650
1 4
$a
Computational Intelligence.
$3
768837
650
2 4
$a
Machine Learning.
$3
1137723
650
2 4
$a
Cancer Research.
$3
668358
650
2 4
$a
Health Informatics.
$3
593963
650
2 4
$a
Computer Imaging, Vision, Pattern Recognition and Graphics.
$3
671334
650
2 4
$a
Signal, Image and Speech Processing.
$3
670837
700
1
$a
Kose, Utku.
$e
editor.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1317558
700
1
$a
Alzubi, Jafar.
$e
editor.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1353317
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9789811563201
776
0 8
$i
Printed edition:
$z
9789811563225
776
0 8
$i
Printed edition:
$z
9789811563232
830
0
$a
Studies in Computational Intelligence,
$x
1860-949X ;
$v
564
$3
1253640
856
4 0
$u
https://doi.org/10.1007/978-981-15-6321-8
912
$a
ZDB-2-INR
912
$a
ZDB-2-SXIT
950
$a
Intelligent Technologies and Robotics (SpringerNature-42732)
950
$a
Intelligent Technologies and Robotics (R0) (SpringerNature-43728)
based on 0 review(s)
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login