Saved in:
Title: | Computerized Systems for Diagnosis and Treatment of COVID-19 |
---|---|
From: |
edited by Joao Alexandre Lobo Marques, Simon James Fong.
|
Person: |
Lobo Marques, Joao Alexandre.
Fong, Simon James. editor. |
Corporate Author: | |
Other Authors: | , |
Format: | Electronic eBook |
Language: | English |
Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2023.
|
Edition: | 1st ed. 2023. |
Subjects: | |
Online Access: | https://doi.org/10.1007/978-3-031-30788-1 |
Summary: | This book describes the application of signal and image processing technologies, artificial intelligence, and machine learning techniques to support Covid-19 diagnosis and treatment. The book focuses on two main applications: critical diagnosis requiring high precision and speed, and treatment of symptoms, including those affecting the cardiovascular and neurological systems. The areas discussed in this book range from signal processing, time series analysis, and image segmentation to detection and classification. Technical approaches include deep learning, transfer learning, transformers, AutoML, and other machine learning techniques that can be considered not only for Covid-19 issues but also for different medical applications, with slight adjustments to the problem under study. The Covid-19 pandemic has impacted the entire world and changed how societies and individuals interact. Due to the high infection and mortality rates, and the multiple consequences of the virusinfection in the human body, the challenges were vast and enormous. These necessitated the integration of different disciplines to address the problems. As a global response, researchers across academia and industry made several developments to provide computational solutions to support epidemiologic, managerial, and health/medical decisions. To that end, this book provides state-of-the-art information on the most advanced solutions. |
Physical Description: | 1 Online-Ressource (VI, 209 p. 91 illus., 67 illus. in color.) |
ISBN: | 9783031307881 |
Staff View
MARC
LEADER | 00000nam a22000005i 4500 | ||
---|---|---|---|
001 | ZDB-2-SBL-978-3-031-30788-1 | ||
003 | DE-He213 | ||
005 | 20240628103807.0 | ||
007 | cr nn 008mamaa | ||
008 | 230626s2023 sz | o |||| 0|eng d | ||
020 | |a 9783031307881 |9 978-3-031-30788-1 | ||
024 | 7 | |a 10.1007/978-3-031-30788-1 |2 doi | |
050 | 4 | |a R856-857 | |
072 | 7 | |a MQW |2 bicssc | |
072 | 7 | |a TEC059000 |2 bisacsh | |
072 | 7 | |a MQW |2 thema | |
082 | 7 | |a 610.28 |2 23 | |
245 | 1 | 0 | |a Computerized Systems for Diagnosis and Treatment of COVID-19 |h [electronic resource] / |c edited by Joao Alexandre Lobo Marques, Simon James Fong. |
250 | |a 1st ed. 2023. | ||
264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2023. | |
300 | |a 1 Online-Ressource (VI, 209 p. 91 illus., 67 illus. in color.) | ||
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 | ||
505 | 0 | |a Clinical impact of automatic diagnostic systems -- Lung segmentation from XRay -- Lung segmentation from CT Scan -- Covid Automatic Diagnostic based on XRay -- Covid Automatic Diagnostic based on CTScan -- Cardiovascular analysis of covid patients based on ECG -- Cognitive analysis of covid patients based on EEG -- AI Controlled Mechanical Ventilator for COVID-19 patients. | |
520 | |a This book describes the application of signal and image processing technologies, artificial intelligence, and machine learning techniques to support Covid-19 diagnosis and treatment. The book focuses on two main applications: critical diagnosis requiring high precision and speed, and treatment of symptoms, including those affecting the cardiovascular and neurological systems. The areas discussed in this book range from signal processing, time series analysis, and image segmentation to detection and classification. Technical approaches include deep learning, transfer learning, transformers, AutoML, and other machine learning techniques that can be considered not only for Covid-19 issues but also for different medical applications, with slight adjustments to the problem under study. The Covid-19 pandemic has impacted the entire world and changed how societies and individuals interact. Due to the high infection and mortality rates, and the multiple consequences of the virusinfection in the human body, the challenges were vast and enormous. These necessitated the integration of different disciplines to address the problems. As a global response, researchers across academia and industry made several developments to provide computational solutions to support epidemiologic, managerial, and health/medical decisions. To that end, this book provides state-of-the-art information on the most advanced solutions. | ||
650 | 0 | |a Biomedical engineering. | |
650 | 0 | |a Therapeutics. | |
650 | 0 | |a Diagnosis. | |
650 | 0 | |a Diseases. | |
650 | 0 | |a Biophysics. | |
650 | 1 | 4 | |a Biomedical Engineering and Bioengineering. |
650 | 2 | 4 | |a Therapeutics. |
650 | 2 | 4 | |a Diagnosis. |
650 | 2 | 4 | |a Diseases. |
650 | 2 | 4 | |a Bioanalysis and Bioimaging. |
700 | 1 | |a Lobo Marques, Joao Alexandre. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
700 | 1 | |a Fong, Simon James. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
710 | 2 | |a SpringerLink (Online service) | |
773 | 0 | |t Springer Nature eBook | |
776 | 0 | 8 | |i Printed edition: |z 9783031307874 |
776 | 0 | 8 | |i Printed edition: |z 9783031307898 |
776 | 0 | 8 | |i Printed edition: |z 9783031307904 |
966 | 4 | 0 | |l DE-355 |p ZDB-2-SBL |q UBG_PDA_SBL |u https://doi.org/10.1007/978-3-031-30788-1 |3 Volltext |
912 | |a ZDB-2-SBL | ||
912 | |a ZDB-2-SXB | ||
950 | |a Biomedical and Life Sciences (SpringerNature-11642) | ||
950 | |a Biomedical and Life Sciences (R0) (SpringerNature-43708) | ||
912 | |a ZDB-2-SBL | ||
049 | |a DE-355 |
Record in the Search Index
DE-BY-UBR_katkey | ZDB-2-SBL-978-3-031-30788-1 |
---|---|
_version_ | 1835726564039327744 |
adam_text | |
any_adam_object | |
author2 | Lobo Marques, Joao Alexandre Fong, Simon James |
author2_role | edt edt |
author2_variant | m j a l mja mjal s j f sj sjf |
author_corporate | SpringerLink (Online service) |
author_corporate_role | |
author_facet | Lobo Marques, Joao Alexandre Fong, Simon James SpringerLink (Online service) |
building | Verbundindex |
bvnumber | localUBR |
callnumber-first | R - Medicine |
callnumber-label | R856-857 |
callnumber-raw | R856-857 |
callnumber-search | R856-857 |
callnumber-sort | R 3856 3857 |
callnumber-subject | R - General Medicine |
collection | ZDB-2-SBL ZDB-2-SXB |
contents | Clinical impact of automatic diagnostic systems -- Lung segmentation from XRay -- Lung segmentation from CT Scan -- Covid Automatic Diagnostic based on XRay -- Covid Automatic Diagnostic based on CTScan -- Cardiovascular analysis of covid patients based on ECG -- Cognitive analysis of covid patients based on EEG -- AI Controlled Mechanical Ventilator for COVID-19 patients. |
dewey-full | 610.28 |
dewey-hundreds | 600 - Technology (Applied sciences) |
dewey-ones | 610 - Medicine and health |
dewey-raw | 610.28 |
dewey-search | 610.28 |
dewey-sort | 3610.28 |
dewey-tens | 610 - Medicine and health |
discipline | Medizin |
edition | 1st ed. 2023. |
format | Electronic eBook |
fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03783nam a22005535i 4500</leader><controlfield tag="001">ZDB-2-SBL-978-3-031-30788-1</controlfield><controlfield tag="003">DE-He213</controlfield><controlfield tag="005">20240628103807.0</controlfield><controlfield tag="007">cr nn 008mamaa</controlfield><controlfield tag="008">230626s2023 sz | o |||| 0|eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783031307881</subfield><subfield code="9">978-3-031-30788-1</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-3-031-30788-1</subfield><subfield code="2">doi</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">R856-857</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">MQW</subfield><subfield code="2">bicssc</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">TEC059000</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">MQW</subfield><subfield code="2">thema</subfield></datafield><datafield tag="082" ind1="7" ind2=" "><subfield code="a">610.28</subfield><subfield code="2">23</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Computerized Systems for Diagnosis and Treatment of COVID-19</subfield><subfield code="h">[electronic resource] /</subfield><subfield code="c">edited by Joao Alexandre Lobo Marques, Simon James Fong.</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st ed. 2023.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cham :</subfield><subfield code="b">Springer International Publishing :</subfield><subfield code="b">Imprint: Springer,</subfield><subfield code="c">2023.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (VI, 209 p. 91 illus., 67 illus. in color.) </subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="347" ind1=" " ind2=" "><subfield code="a">text file</subfield><subfield code="b">PDF</subfield><subfield code="2">rda</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="a">Clinical impact of automatic diagnostic systems -- Lung segmentation from XRay -- Lung segmentation from CT Scan -- Covid Automatic Diagnostic based on XRay -- Covid Automatic Diagnostic based on CTScan -- Cardiovascular analysis of covid patients based on ECG -- Cognitive analysis of covid patients based on EEG -- AI Controlled Mechanical Ventilator for COVID-19 patients.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This book describes the application of signal and image processing technologies, artificial intelligence, and machine learning techniques to support Covid-19 diagnosis and treatment. The book focuses on two main applications: critical diagnosis requiring high precision and speed, and treatment of symptoms, including those affecting the cardiovascular and neurological systems. The areas discussed in this book range from signal processing, time series analysis, and image segmentation to detection and classification. Technical approaches include deep learning, transfer learning, transformers, AutoML, and other machine learning techniques that can be considered not only for Covid-19 issues but also for different medical applications, with slight adjustments to the problem under study. The Covid-19 pandemic has impacted the entire world and changed how societies and individuals interact. Due to the high infection and mortality rates, and the multiple consequences of the virusinfection in the human body, the challenges were vast and enormous. These necessitated the integration of different disciplines to address the problems. As a global response, researchers across academia and industry made several developments to provide computational solutions to support epidemiologic, managerial, and health/medical decisions. To that end, this book provides state-of-the-art information on the most advanced solutions.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Biomedical engineering.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Therapeutics.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Diagnosis.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Diseases.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Biophysics.</subfield></datafield><datafield tag="650" ind1="1" ind2="4"><subfield code="a">Biomedical Engineering and Bioengineering.</subfield></datafield><datafield tag="650" ind1="2" ind2="4"><subfield code="a">Therapeutics.</subfield></datafield><datafield tag="650" ind1="2" ind2="4"><subfield code="a">Diagnosis.</subfield></datafield><datafield tag="650" ind1="2" ind2="4"><subfield code="a">Diseases.</subfield></datafield><datafield tag="650" ind1="2" ind2="4"><subfield code="a">Bioanalysis and Bioimaging.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lobo Marques, Joao Alexandre.</subfield><subfield code="e">editor.</subfield><subfield code="4">edt</subfield><subfield code="4">http://id.loc.gov/vocabulary/relators/edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Fong, Simon James.</subfield><subfield code="e">editor.</subfield><subfield code="4">edt</subfield><subfield code="4">http://id.loc.gov/vocabulary/relators/edt</subfield></datafield><datafield tag="710" ind1="2" ind2=" "><subfield code="a">SpringerLink (Online service)</subfield></datafield><datafield tag="773" ind1="0" ind2=" "><subfield code="t">Springer Nature eBook</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Printed edition:</subfield><subfield code="z">9783031307874</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Printed edition:</subfield><subfield code="z">9783031307898</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Printed edition:</subfield><subfield code="z">9783031307904</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-355</subfield><subfield code="p">ZDB-2-SBL</subfield><subfield code="q">UBG_PDA_SBL</subfield><subfield code="u">https://doi.org/10.1007/978-3-031-30788-1</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-SBL</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-SXB</subfield></datafield><datafield tag="950" ind1=" " ind2=" "><subfield code="a">Biomedical and Life Sciences (SpringerNature-11642)</subfield></datafield><datafield tag="950" ind1=" " ind2=" "><subfield code="a">Biomedical and Life Sciences (R0) (SpringerNature-43708)</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-SBL</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-355</subfield></datafield></record></collection> |
id | ZDB-2-SBL-978-3-031-30788-1 |
illustrated | Not Illustrated |
indexdate | 2025-06-23T13:27:56Z |
institution | BVB |
isbn | 9783031307881 |
language | English |
open_access_boolean | |
owner | DE-355 DE-BY-UBR |
owner_facet | DE-355 DE-BY-UBR |
physical | 1 Online-Ressource (VI, 209 p. 91 illus., 67 illus. in color.) |
psigel | ZDB-2-SBL UBG_PDA_SBL ZDB-2-SBL ZDB-2-SXB |
publishDate | 2023 |
publishDateSearch | 2023 |
publishDateSort | 2023 |
publisher | Springer International Publishing : Imprint: Springer, |
record_format | marc |
spelling | Computerized Systems for Diagnosis and Treatment of COVID-19 [electronic resource] / edited by Joao Alexandre Lobo Marques, Simon James Fong. 1st ed. 2023. Cham : Springer International Publishing : Imprint: Springer, 2023. 1 Online-Ressource (VI, 209 p. 91 illus., 67 illus. in color.) text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Clinical impact of automatic diagnostic systems -- Lung segmentation from XRay -- Lung segmentation from CT Scan -- Covid Automatic Diagnostic based on XRay -- Covid Automatic Diagnostic based on CTScan -- Cardiovascular analysis of covid patients based on ECG -- Cognitive analysis of covid patients based on EEG -- AI Controlled Mechanical Ventilator for COVID-19 patients. This book describes the application of signal and image processing technologies, artificial intelligence, and machine learning techniques to support Covid-19 diagnosis and treatment. The book focuses on two main applications: critical diagnosis requiring high precision and speed, and treatment of symptoms, including those affecting the cardiovascular and neurological systems. The areas discussed in this book range from signal processing, time series analysis, and image segmentation to detection and classification. Technical approaches include deep learning, transfer learning, transformers, AutoML, and other machine learning techniques that can be considered not only for Covid-19 issues but also for different medical applications, with slight adjustments to the problem under study. The Covid-19 pandemic has impacted the entire world and changed how societies and individuals interact. Due to the high infection and mortality rates, and the multiple consequences of the virusinfection in the human body, the challenges were vast and enormous. These necessitated the integration of different disciplines to address the problems. As a global response, researchers across academia and industry made several developments to provide computational solutions to support epidemiologic, managerial, and health/medical decisions. To that end, this book provides state-of-the-art information on the most advanced solutions. Biomedical engineering. Therapeutics. Diagnosis. Diseases. Biophysics. Biomedical Engineering and Bioengineering. Bioanalysis and Bioimaging. Lobo Marques, Joao Alexandre. editor. edt http://id.loc.gov/vocabulary/relators/edt Fong, Simon James. editor. edt http://id.loc.gov/vocabulary/relators/edt SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031307874 Printed edition: 9783031307898 Printed edition: 9783031307904 |
spellingShingle | Computerized Systems for Diagnosis and Treatment of COVID-19 Clinical impact of automatic diagnostic systems -- Lung segmentation from XRay -- Lung segmentation from CT Scan -- Covid Automatic Diagnostic based on XRay -- Covid Automatic Diagnostic based on CTScan -- Cardiovascular analysis of covid patients based on ECG -- Cognitive analysis of covid patients based on EEG -- AI Controlled Mechanical Ventilator for COVID-19 patients. Biomedical engineering. Therapeutics. Diagnosis. Diseases. Biophysics. Biomedical Engineering and Bioengineering. Bioanalysis and Bioimaging. |
title | Computerized Systems for Diagnosis and Treatment of COVID-19 |
title_auth | Computerized Systems for Diagnosis and Treatment of COVID-19 |
title_exact_search | Computerized Systems for Diagnosis and Treatment of COVID-19 |
title_full | Computerized Systems for Diagnosis and Treatment of COVID-19 [electronic resource] / edited by Joao Alexandre Lobo Marques, Simon James Fong. |
title_fullStr | Computerized Systems for Diagnosis and Treatment of COVID-19 [electronic resource] / edited by Joao Alexandre Lobo Marques, Simon James Fong. |
title_full_unstemmed | Computerized Systems for Diagnosis and Treatment of COVID-19 [electronic resource] / edited by Joao Alexandre Lobo Marques, Simon James Fong. |
title_short | Computerized Systems for Diagnosis and Treatment of COVID-19 |
title_sort | computerized systems for diagnosis and treatment of covid 19 |
topic | Biomedical engineering. Therapeutics. Diagnosis. Diseases. Biophysics. Biomedical Engineering and Bioengineering. Bioanalysis and Bioimaging. |
topic_facet | Biomedical engineering. Therapeutics. Diagnosis. Diseases. Biophysics. Biomedical Engineering and Bioengineering. Bioanalysis and Bioimaging. |
work_keys_str_mv | AT lobomarquesjoaoalexandre computerizedsystemsfordiagnosisandtreatmentofcovid19 AT fongsimonjames computerizedsystemsfordiagnosisandtreatmentofcovid19 AT springerlinkonlineservice computerizedsystemsfordiagnosisandtreatmentofcovid19 |