Journal article 342 views 38 downloads
Editorial: Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA)
Frontiers in Big Data, Volume: 5, Start page: 863060
Swansea University Author: Shuai Li
-
PDF | Version of Record
Copyright © 2022 Zhang, Li, Cattani and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY)
Download (94.63KB)
DOI (Published version): 10.3389/fdata.2022.863060
Abstract
Editorial: Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA)
Published in: | Frontiers in Big Data |
---|---|
ISSN: | 2624-909X |
Published: |
Frontiers Media S.A.
2022
|
Online Access: |
Check full text
|
URI: | https://cronfa.swan.ac.uk/Record/cronfa59642 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
first_indexed |
2022-03-16T14:58:04Z |
---|---|
last_indexed |
2022-03-17T04:28:57Z |
id |
cronfa59642 |
recordtype |
SURis |
fullrecord |
<?xml version="1.0"?><rfc1807><datestamp>2022-03-16T14:59:25.3407845</datestamp><bib-version>v2</bib-version><id>59642</id><entry>2022-03-16</entry><title>Editorial: Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA)</title><swanseaauthors><author><sid>42ff9eed09bcd109fbbe484a0f99a8a8</sid><ORCID>0000-0001-8316-5289</ORCID><firstname>Shuai</firstname><surname>Li</surname><name>Shuai Li</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2022-03-16</date><deptcode>MECH</deptcode><abstract/><type>Journal Article</type><journal>Frontiers in Big Data</journal><volume>5</volume><journalNumber/><paginationStart>863060</paginationStart><paginationEnd/><publisher>Frontiers Media S.A.</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2624-909X</issnElectronic><keywords>deep learning, biomedical information analysis, magnetic resonance imaging, social media, omics, surface electromyography, optical character recognition, computed tomography</keywords><publishedDay>1</publishedDay><publishedMonth>3</publishedMonth><publishedYear>2022</publishedYear><publishedDate>2022-03-01</publishedDate><doi>10.3389/fdata.2022.863060</doi><url/><notes/><college>COLLEGE NANME</college><department>Mechanical Engineering</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MECH</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2022-03-16T14:59:25.3407845</lastEdited><Created>2022-03-16T14:54:39.8842240</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering</level></path><authors><author><firstname>Yu-Dong</firstname><surname>Zhang</surname><order>1</order></author><author><firstname>Shuai</firstname><surname>Li</surname><orcid>0000-0001-8316-5289</orcid><order>2</order></author><author><firstname>Carlo</firstname><surname>Cattani</surname><order>3</order></author><author><firstname>Shui-Hua</firstname><surname>Wang</surname><order>4</order></author></authors><documents><document><filename>59642__22616__b0c17c7b9a5d4fc19db1cf1e49ed6525.pdf</filename><originalFilename>59642.pdf</originalFilename><uploaded>2022-03-16T14:57:25.6807557</uploaded><type>Output</type><contentLength>96903</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>Copyright © 2022 Zhang, Li, Cattani and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY)</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807> |
spelling |
2022-03-16T14:59:25.3407845 v2 59642 2022-03-16 Editorial: Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA) 42ff9eed09bcd109fbbe484a0f99a8a8 0000-0001-8316-5289 Shuai Li Shuai Li true false 2022-03-16 MECH Journal Article Frontiers in Big Data 5 863060 Frontiers Media S.A. 2624-909X deep learning, biomedical information analysis, magnetic resonance imaging, social media, omics, surface electromyography, optical character recognition, computed tomography 1 3 2022 2022-03-01 10.3389/fdata.2022.863060 COLLEGE NANME Mechanical Engineering COLLEGE CODE MECH Swansea University 2022-03-16T14:59:25.3407845 2022-03-16T14:54:39.8842240 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering Yu-Dong Zhang 1 Shuai Li 0000-0001-8316-5289 2 Carlo Cattani 3 Shui-Hua Wang 4 59642__22616__b0c17c7b9a5d4fc19db1cf1e49ed6525.pdf 59642.pdf 2022-03-16T14:57:25.6807557 Output 96903 application/pdf Version of Record true Copyright © 2022 Zhang, Li, Cattani and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) true eng http://creativecommons.org/licenses/by/4.0/ |
title |
Editorial: Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA) |
spellingShingle |
Editorial: Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA) Shuai Li |
title_short |
Editorial: Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA) |
title_full |
Editorial: Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA) |
title_fullStr |
Editorial: Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA) |
title_full_unstemmed |
Editorial: Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA) |
title_sort |
Editorial: Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA) |
author_id_str_mv |
42ff9eed09bcd109fbbe484a0f99a8a8 |
author_id_fullname_str_mv |
42ff9eed09bcd109fbbe484a0f99a8a8_***_Shuai Li |
author |
Shuai Li |
author2 |
Yu-Dong Zhang Shuai Li Carlo Cattani Shui-Hua Wang |
format |
Journal article |
container_title |
Frontiers in Big Data |
container_volume |
5 |
container_start_page |
863060 |
publishDate |
2022 |
institution |
Swansea University |
issn |
2624-909X |
doi_str_mv |
10.3389/fdata.2022.863060 |
publisher |
Frontiers Media S.A. |
college_str |
Faculty of Science and Engineering |
hierarchytype |
|
hierarchy_top_id |
facultyofscienceandengineering |
hierarchy_top_title |
Faculty of Science and Engineering |
hierarchy_parent_id |
facultyofscienceandengineering |
hierarchy_parent_title |
Faculty of Science and Engineering |
department_str |
School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering |
document_store_str |
1 |
active_str |
0 |
published_date |
2022-03-01T04:17:07Z |
_version_ |
1763754143584878592 |
score |
11.016258 |