Deep Learning in Healthcare: Paradigms and Applications

This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diag...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Chen, Yen-Wei, Jain, Lakhmi C
Format: Buch
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume 171
creator Chen, Yen-Wei
Jain, Lakhmi C
description This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems.Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data.Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.
doi_str_mv 10.1007/978-3-030-32606-7
format Book
fullrecord <record><control><sourceid>proquest_askew</sourceid><recordid>TN_cdi_askewsholts_vlebooks_9783030326067</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>EBC5982465</sourcerecordid><originalsourceid>FETCH-LOGICAL-a14727-994a4eaf36a6bda1cf4bfdc783f41870fa540c13d1383f03fe72729a9dc72c73</originalsourceid><addsrcrecordid>eNpVkE9PAjEQxevfiMgHMF64GQ-Vmba7bY-KKCYkXvTclGUqyGYXt6t-fQurB06TvPm9lzfD2CXCLQLokdWGSw4SuBQ55FwfsEHSZFJ2gj5kPTS54UqBOdrbZXD8v5NWnbJzRGE0JkKcsUGMHwAghLQI2GNXD0Sb4Yx8U62q9-GqGk7Jl-2y8A1dsJPgy0iDv9lnb4-T1_GUz16ensd3M-5RaaG5tcor8kHmPp8vPBZBzcOiSI2CQqMh-ExBgXKBMkkgAyWXsN4mRhRa9tlNl-vjmn7isi7b6L5Lmtf1Orq9qxM76ti4aVJhalxHIbjt37a0ky7xbmdwW8d159g09ecXxdbtgguq2saXbnI_zqwRKs_kLzP9Yqo</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>book</recordtype><pqid>EBC5982465</pqid></control><display><type>book</type><title>Deep Learning in Healthcare: Paradigms and Applications</title><source>Springer Books</source><creator>Chen, Yen-Wei ; Jain, Lakhmi C</creator><contributor>Jain, Lakhmi C. ; Chen, Yen-Wei</contributor><creatorcontrib>Chen, Yen-Wei ; Jain, Lakhmi C ; Jain, Lakhmi C. ; Chen, Yen-Wei</creatorcontrib><description>This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems.Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data.Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.</description><edition>1st ed. 2020.</edition><identifier>ISSN: 1868-4394</identifier><identifier>ISBN: 9783030326050</identifier><identifier>ISBN: 3030326055</identifier><identifier>EISSN: 1868-4408</identifier><identifier>EISBN: 9783030326067</identifier><identifier>EISBN: 3030326063</identifier><identifier>DOI: 10.1007/978-3-030-32606-7</identifier><identifier>OCLC: 1128719782</identifier><language>eng</language><publisher>Cham: Springer International Publishing AG</publisher><subject>Artificial Intelligence ; Computational Intelligence ; Engineering ; Health Informatics</subject><creationdate>2019</creationdate><tpages>225</tpages><format>225</format><rights>Springer Nature Switzerland AG 2020</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><relation>Intelligent Systems Reference Library</relation></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://media.springernature.com/w306/springer-static/cover-hires/book/978-3-030-32606-7</thumbnail><linktohtml>$$Uhttps://link.springer.com/10.1007/978-3-030-32606-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>306,780,784,786,27925,38255,42511</link.rule.ids></links><search><contributor>Jain, Lakhmi C.</contributor><contributor>Chen, Yen-Wei</contributor><creatorcontrib>Chen, Yen-Wei</creatorcontrib><creatorcontrib>Jain, Lakhmi C</creatorcontrib><title>Deep Learning in Healthcare: Paradigms and Applications</title><description>This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems.Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data.Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.</description><subject>Artificial Intelligence</subject><subject>Computational Intelligence</subject><subject>Engineering</subject><subject>Health Informatics</subject><issn>1868-4394</issn><issn>1868-4408</issn><isbn>9783030326050</isbn><isbn>3030326055</isbn><isbn>9783030326067</isbn><isbn>3030326063</isbn><fulltext>true</fulltext><rsrctype>book</rsrctype><creationdate>2019</creationdate><recordtype>book</recordtype><sourceid/><recordid>eNpVkE9PAjEQxevfiMgHMF64GQ-Vmba7bY-KKCYkXvTclGUqyGYXt6t-fQurB06TvPm9lzfD2CXCLQLokdWGSw4SuBQ55FwfsEHSZFJ2gj5kPTS54UqBOdrbZXD8v5NWnbJzRGE0JkKcsUGMHwAghLQI2GNXD0Sb4Yx8U62q9-GqGk7Jl-2y8A1dsJPgy0iDv9lnb4-T1_GUz16ensd3M-5RaaG5tcor8kHmPp8vPBZBzcOiSI2CQqMh-ExBgXKBMkkgAyWXsN4mRhRa9tlNl-vjmn7isi7b6L5Lmtf1Orq9qxM76ti4aVJhalxHIbjt37a0ky7xbmdwW8d159g09ecXxdbtgguq2saXbnI_zqwRKs_kLzP9Yqo</recordid><startdate>2019</startdate><enddate>2019</enddate><creator>Chen, Yen-Wei</creator><creator>Jain, Lakhmi C</creator><general>Springer International Publishing AG</general><general>Springer International Publishing</general><scope/></search><sort><creationdate>2019</creationdate><title>Deep Learning in Healthcare</title><author>Chen, Yen-Wei ; Jain, Lakhmi C</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a14727-994a4eaf36a6bda1cf4bfdc783f41870fa540c13d1383f03fe72729a9dc72c73</frbrgroupid><rsrctype>books</rsrctype><prefilter>books</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Artificial Intelligence</topic><topic>Computational Intelligence</topic><topic>Engineering</topic><topic>Health Informatics</topic><toplevel>online_resources</toplevel><creatorcontrib>Chen, Yen-Wei</creatorcontrib><creatorcontrib>Jain, Lakhmi C</creatorcontrib></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Yen-Wei</au><au>Jain, Lakhmi C</au><au>Jain, Lakhmi C.</au><au>Chen, Yen-Wei</au><format>book</format><genre>book</genre><ristype>BOOK</ristype><btitle>Deep Learning in Healthcare: Paradigms and Applications</btitle><seriestitle>Intelligent Systems Reference Library</seriestitle><date>2019</date><risdate>2019</risdate><volume>171</volume><issn>1868-4394</issn><eissn>1868-4408</eissn><isbn>9783030326050</isbn><isbn>3030326055</isbn><eisbn>9783030326067</eisbn><eisbn>3030326063</eisbn><abstract>This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems.Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data.Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.</abstract><cop>Cham</cop><pub>Springer International Publishing AG</pub><doi>10.1007/978-3-030-32606-7</doi><oclcid>1128719782</oclcid><tpages>225</tpages><edition>1st ed. 2020.</edition></addata></record>
fulltext fulltext
identifier ISSN: 1868-4394
ispartof
issn 1868-4394
1868-4408
language eng
recordid cdi_askewsholts_vlebooks_9783030326067
source Springer Books
subjects Artificial Intelligence
Computational Intelligence
Engineering
Health Informatics
title Deep Learning in Healthcare: Paradigms and Applications
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T22%3A35%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_askew&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=book&rft.btitle=Deep%20Learning%20in%20Healthcare:%20Paradigms%20and%20Applications&rft.au=Chen,%20Yen-Wei&rft.date=2019&rft.volume=171&rft.issn=1868-4394&rft.eissn=1868-4408&rft.isbn=9783030326050&rft.isbn_list=3030326055&rft_id=info:doi/10.1007/978-3-030-32606-7&rft_dat=%3Cproquest_askew%3EEBC5982465%3C/proquest_askew%3E%3Curl%3E%3C/url%3E&rft.eisbn=9783030326067&rft.eisbn_list=3030326063&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=EBC5982465&rft_id=info:pmid/&rfr_iscdi=true