語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Deep learning techniques for biomedi...
~
Dash, Sujata.
FindBook
Google Book
Amazon
博客來
Deep learning techniques for biomedical and health informatics
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Deep learning techniques for biomedical and health informatics/ edited by Sujata Dash ... [et al.].
其他作者:
Dash, Sujata.
出版者:
Cham :Springer International Publishing : : 2020.,
面頁冊數:
xxv, 383 p. :ill., digital ;24 cm.
內容註:
MedNLU: Natural Language Understander for Medical Texts -- Deep Learning Based Biomedical Named Entity Recognition Systems -- Disambiguation Model for Bio-Medical Named Entity Recognition -- Applications of Deep Learning in Healthcare and Biomedicine -- Deep Learning for Clinical Decision Support Systems: A Review from the Panorama of Smart Healthcare -- Review of Machine Learning and Deep Learning based Recommender Systems for Health Informatics -- Deep Learning and Explainable AI in Healthcare using EHR -- Deep Learning for Analysis of Electronic Heath Records -- Bioinformatics Using Deep Architecture -- Intelligent, Secure Big Health Data Management using Deep Learning and Blockchain Technology: An Overview -- Malaria Disease Detection using CNN Technique with SGD, RMSprop and ADAM Optimizers -- Deep Reinforcement Learning based Personalized Health Recommendations.
Contained By:
Springer eBooks
標題:
Machine learning. -
電子資源:
https://doi.org/10.1007/978-3-030-33966-1
ISBN:
9783030339661
Deep learning techniques for biomedical and health informatics
Deep learning techniques for biomedical and health informatics
[electronic resource] /edited by Sujata Dash ... [et al.]. - Cham :Springer International Publishing :2020. - xxv, 383 p. :ill., digital ;24 cm. - Studies in big data,v.682197-6503 ;. - Studies in big data ;v.68..
MedNLU: Natural Language Understander for Medical Texts -- Deep Learning Based Biomedical Named Entity Recognition Systems -- Disambiguation Model for Bio-Medical Named Entity Recognition -- Applications of Deep Learning in Healthcare and Biomedicine -- Deep Learning for Clinical Decision Support Systems: A Review from the Panorama of Smart Healthcare -- Review of Machine Learning and Deep Learning based Recommender Systems for Health Informatics -- Deep Learning and Explainable AI in Healthcare using EHR -- Deep Learning for Analysis of Electronic Heath Records -- Bioinformatics Using Deep Architecture -- Intelligent, Secure Big Health Data Management using Deep Learning and Blockchain Technology: An Overview -- Malaria Disease Detection using CNN Technique with SGD, RMSprop and ADAM Optimizers -- Deep Reinforcement Learning based Personalized Health Recommendations.
This book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life by efficiently analyzing abundant biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it was common to have a domain expert to develop a model for biomedical or health care applications; however, recent advances in the representation of learning algorithms (deep learning techniques) make it possible to automatically recognize the patterns and represent the given data for the development of such model. This book allows new researchers and practitioners working in the field to quickly understand the best-performing methods. It also enables them to compare different approaches and carry forward their research in an important area that has a direct impact on improving the human life and health. It is intended for researchers, academics, industry professionals, and those at technical institutes and R&D organizations, as well as students working in the fields of machine learning, deep learning, biomedical engineering, health informatics, and related fields.
ISBN: 9783030339661
Standard No.: 10.1007/978-3-030-33966-1doiSubjects--Topical Terms:
533906
Machine learning.
LC Class. No.: Q325.5 / .D447 2020
Dewey Class. No.: 006.31
Deep learning techniques for biomedical and health informatics
LDR
:03248nmm a2200337 a 4500
001
2214676
003
DE-He213
005
20200317161334.0
006
m d
007
cr nn 008maaau
008
201118s2020 sz s 0 eng d
020
$a
9783030339661
$q
(electronic bk.)
020
$a
9783030339654
$q
(paper)
024
7
$a
10.1007/978-3-030-33966-1
$2
doi
035
$a
978-3-030-33966-1
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
Q325.5
$b
.D447 2020
072
7
$a
UYQ
$2
bicssc
072
7
$a
TEC009000
$2
bisacsh
072
7
$a
UYQ
$2
thema
082
0 4
$a
006.31
$2
23
090
$a
Q325.5
$b
.D311 2020
245
0 0
$a
Deep learning techniques for biomedical and health informatics
$h
[electronic resource] /
$c
edited by Sujata Dash ... [et al.].
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2020.
300
$a
xxv, 383 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Studies in big data,
$x
2197-6503 ;
$v
v.68
505
0
$a
MedNLU: Natural Language Understander for Medical Texts -- Deep Learning Based Biomedical Named Entity Recognition Systems -- Disambiguation Model for Bio-Medical Named Entity Recognition -- Applications of Deep Learning in Healthcare and Biomedicine -- Deep Learning for Clinical Decision Support Systems: A Review from the Panorama of Smart Healthcare -- Review of Machine Learning and Deep Learning based Recommender Systems for Health Informatics -- Deep Learning and Explainable AI in Healthcare using EHR -- Deep Learning for Analysis of Electronic Heath Records -- Bioinformatics Using Deep Architecture -- Intelligent, Secure Big Health Data Management using Deep Learning and Blockchain Technology: An Overview -- Malaria Disease Detection using CNN Technique with SGD, RMSprop and ADAM Optimizers -- Deep Reinforcement Learning based Personalized Health Recommendations.
520
$a
This book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life by efficiently analyzing abundant biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it was common to have a domain expert to develop a model for biomedical or health care applications; however, recent advances in the representation of learning algorithms (deep learning techniques) make it possible to automatically recognize the patterns and represent the given data for the development of such model. This book allows new researchers and practitioners working in the field to quickly understand the best-performing methods. It also enables them to compare different approaches and carry forward their research in an important area that has a direct impact on improving the human life and health. It is intended for researchers, academics, industry professionals, and those at technical institutes and R&D organizations, as well as students working in the fields of machine learning, deep learning, biomedical engineering, health informatics, and related fields.
650
0
$a
Machine learning.
$3
533906
650
0
$a
Artificial intelligence
$x
Medical applications.
$3
900591
650
1 4
$a
Computational Intelligence.
$3
1001631
650
2 4
$a
Data Engineering.
$3
3409361
650
2 4
$a
Biomedical Engineering and Bioengineering.
$3
3381533
650
2 4
$a
Big Data.
$3
3134868
650
2 4
$a
Artificial Intelligence.
$3
769149
700
1
$a
Dash, Sujata.
$3
3445423
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
830
0
$a
Studies in big data ;
$v
v.68.
$3
3445424
856
4 0
$u
https://doi.org/10.1007/978-3-030-33966-1
950
$a
Intelligent Technologies and Robotics (Springer-42732)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9389584
電子資源
11.線上閱覽_V
電子書
EB Q325.5 .D447 2020
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入