國立虎尾科技大學 |

Rhythms in Healthcare

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Rhythms in Healthcare/ edited by M. Shamim Kaiser, Mufti Mahmud, Shamim Al Mamun.
其他作者:	Al Mamun, Shamim.
面頁冊數:	XV, 161 p. 52 illus., 48 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Machine Learning. -
電子資源:	https://doi.org/10.1007/978-981-19-4189-4
ISBN:	9789811941894

Rhythms in Healthcare
Rhythms in Healthcare[electronic resource] /edited by M. Shamim Kaiser, Mufti Mahmud, Shamim Al Mamun. - 1st ed. 2022. - XV, 161 p. 52 illus., 48 illus. in color.online resource. - Studies in Rhythm Engineering,2524-5554. - Studies in Rhythm Engineering,.

Is Biological rhythm associated with the mortality of COVID-19? -- Deep Learning in Biomedical devices: Perspectives, Applications and Challenges -- Effect of 3D-Multiple object Tracking training on manual dexterity in elderly adults with dementia and mild cognitive impairment -- Rhythmic Pattern of EEG for Identifying Schizophrenia -- Prior Prediction and Management of Autism in Child through Behavioral Analysis using Machine Learning Approach -- DNN and LiDAR Sensor Based Crowd Avoidance Method for Nurse-Following Robot in Healthcare.

This book provides an insightful review and methodological contribution about future healthcare system. It also provides a space for creating and designing techniques for effective sensing, processing, and analysis of patient health situations based on bio-signal processing. Additionally, it discusses novel methods and algorithms which are needed to overcome limitations in current rhythmic bio-signals models. It also discusses solutions and systems needed to efficiently evaluate and process real-time data. The book is useful for wide range of users, including students, research scientists, teachers, and practitioners working in the field of heath informatics, neuroscience, biomedical engineering, and medical image processing and diagnosis.

ISBN: 9789811941894

Standard No.: 10.1007/978-981-19-4189-4doiSubjects--Topical Terms:

1137723
Machine Learning.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Rhythms in Healthcare
LDR:02731nam a22004095i 4500 001 1083129
003 DE-He213
005 20220913094820.0
007 cr nn 008mamaa
008 221228s2022 si | s |||| 0|eng d
020 $a 9789811941894 $9 978-981-19-4189-4
024 7 $a 10.1007/978-981-19-4189-4 $2 doi
035 $a 978-981-19-4189-4
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 Rhythms in Healthcare $h [electronic resource] / $c edited by M. Shamim Kaiser, Mufti Mahmud, Shamim Al Mamun.
250 $a 1st ed. 2022.
264 1 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2022.
300 $a XV, 161 p. 52 illus., 48 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 Rhythm Engineering, $x 2524-5554
505 0 $a Is Biological rhythm associated with the mortality of COVID-19? -- Deep Learning in Biomedical devices: Perspectives, Applications and Challenges -- Effect of 3D-Multiple object Tracking training on manual dexterity in elderly adults with dementia and mild cognitive impairment -- Rhythmic Pattern of EEG for Identifying Schizophrenia -- Prior Prediction and Management of Autism in Child through Behavioral Analysis using Machine Learning Approach -- DNN and LiDAR Sensor Based Crowd Avoidance Method for Nurse-Following Robot in Healthcare.
520 $a This book provides an insightful review and methodological contribution about future healthcare system. It also provides a space for creating and designing techniques for effective sensing, processing, and analysis of patient health situations based on bio-signal processing. Additionally, it discusses novel methods and algorithms which are needed to overcome limitations in current rhythmic bio-signals models. It also discusses solutions and systems needed to efficiently evaluate and process real-time data. The book is useful for wide range of users, including students, research scientists, teachers, and practitioners working in the field of heath informatics, neuroscience, biomedical engineering, and medical image processing and diagnosis.
650 2 4 $a Machine Learning. $3 1137723
650 2 4 $a Health Informatics. $3 593963
650 2 4 $a Artificial Intelligence. $3 646849
650 1 4 $a Computational Intelligence. $3 768837
650 0 $a Machine learning. $3 561253
650 0 $a Medical informatics. $3 583858
650 0 $a Artificial intelligence. $3 559380
650 0 $a Computational intelligence. $3 568984
700 1 $a Al Mamun, Shamim. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1389030
700 1 $a Mahmud, Mufti. $e editor. $1 https://orcid.org/0000-0002-2037-8348 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1326098
700 1 $a Kaiser, M. Shamim. $e editor. $1 https://orcid.org/0000-0002-4604-5461 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1326100
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811941887
776 0 8 $i Printed edition: $z 9789811941900
776 0 8 $i Printed edition: $z 9789811941917
830 0 $a Studies in Rhythm Engineering, $x 2524-5554 $3 1350238
856 4 0 $u https://doi.org/10.1007/978-981-19-4189-4
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)