Data Science for COVID-19 : (Record no. 36177)

MARC details
000 -LEADER
fixed length control field 11034nam a22004933i 4500
001 - CONTROL NUMBER
control field EBC6789182
003 - CONTROL NUMBER IDENTIFIER
control field MiAaPQ
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220524155653.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
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007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220504s2021 xx o ||||0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780323907705
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9780323907699
035 ## - SYSTEM CONTROL NUMBER
System control number (MiAaPQ)EBC6789182
035 ## - SYSTEM CONTROL NUMBER
System control number (Au-PeEL)EBL6789182
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1283850473
040 ## - CATALOGING SOURCE
Original cataloging agency MiAaPQ
Language of cataloging eng
Description conventions rda
-- pn
Transcribing agency MiAaPQ
Modifying agency MiAaPQ
082 0# - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 614.592414
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Kose, Utku.
245 10 - TITLE STATEMENT
Title Data Science for COVID-19 :
Remainder of title Volume 2: Societal and Medical Perspectives.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture San Diego :
Name of producer, publisher, distributor, manufacturer Elsevier Science & Technology,
Date of production, publication, distribution, manufacture, or copyright notice 2021.
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Date of production, publication, distribution, manufacture, or copyright notice �2022.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (814 pages)
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Front Cover -- Data Science for COVID-19 -- Advances in Biomedical Informatics Data Science for COVID-19: Volume Two: Societal and Medical Perspectives -- Copyright -- Contents -- Contributors -- Foreword -- Preface -- 1 - Essentials of the COVID-19 coronavirus -- 1. Introduction -- 1.1 Background -- 1.2 Rationale -- 2. Materials and methods -- 2.1 Retrieval of nucleotides and amino acid sequences -- 2.2 Determination of physiochemical properties of the novel coronavirus gene sequences -- 2.3 Determination of guanine-cytosine content of SARS-CoV-2 sequences from 12 endemic countries -- 2.4 Determination of evolutionary distance, mutation pathway, time of gene divergence, and phylogenetic analysis of the novel S ... -- 2.5 Prediction of secondary and tertiary protein folding RNA structure of coronavirus sequences -- 3. Revealed essential features of COVID-19 coronavirus -- 3.1 Essential physical attributes of COVID-19 coronavirus -- 3.1.1 Molecular weight/size of COVID-19 coronavirus -- 3.1.2 Total number of atoms of the COVID-19 coronavirus -- 3.1.3 Amino acid side chain constituents of the COVID-19 coronavirus -- 3.1.4 Aliphatic (side chain) index of the COVID-19 coronavirus -- 3.1.5 Instability index of the COVID-19 coronavirus -- 3.1.6 Guanine-cytosine content of the COVID-19 coronavirus -- 3.1.7 Half-life of the COVID-19 coronavirus in human reticulocytes -- 3.2 Essential chemical features of the COVID-19 coronavirus -- 3.2.1 Grand hydropathicity of the COVID-19 coronavirus -- 3.2.2 Theoretic isoelectric point (pl) of the COVID-19 coronavirus -- 3.2.3 Extinction/attenuation coefficients of the COVID-19 coronavirus -- 3.2.4 Total number of negatively charged amino acid residues -- 3.2.5 Total number of positively charged amino acid residues -- 3.2.6 Coding regions for COVID-19 viruses -- 3.3 Biological characteristics of the COVID-19 virus.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 3.3.1 Protein coat structure of the COVID-19 coronavirus -- 3.3.2 Primary protein structures of the COVID-19 coronavirus -- 3.3.3 Secondary protein folding structures of the COVID-19 coronavirus -- 3.3.4 Tertiary protein folding structures of the COVID-19 coronavirus -- 3.3.5 Domain architectural composition of the COVID-19 coronavirus -- 3.3.6 Antigen epitope characteristics of the COVID-19 coronavirus -- 3.4 Phylogenetic characterization of the COVID-19 coronavirus -- 3.4.1 Evolutionary distance of the COVID-19 coronavirus -- 3.4.2 Time of genetic divergence and group consensus of the COVID-19 coronavirus -- 3.4.3 Mutation and evolutionary pathway of the COVID-19 coronavirus -- 3.4.4 Genetic polymorphism/single nucleotide polymorphisms -- 3.5 General essential features of the COVID-19 coronavirus -- 3.5.1 Common symptoms of COVID-19 -- 3.5.2 Mode of spread of SARS-CoV-2 infection -- 3.5.3 Diagnosis of SARS-CoV-2 infection -- 3.5.4 Prevailing prophylactic measures -- 3.5.5 Therapeutics/vaccine trials available at the moment -- 3.5.6 Challenges in combating COVID-19 pandemic -- 3.5.7 Any hope for a lasting solution and the future? -- 3.6 Conclusion -- Abbreviations -- References -- 2 - Docking study of transmembrane serine protease type 2 inhibitors for the treatment of COVID-19 -- 1. Introduction -- 2. Materials and methods -- 2.1 Homology modeling and model validation -- 2.2 Molecular docking by AutoDock Vina -- 3. Results -- 3.1 Template identification and sequence alignment -- 3.2 Homology modeling -- 3.3 Active site identification of TMPRSS2 -- 3.4 Molecular docking -- 4. Discussion -- 5. Conclusions -- References -- Further reading -- 3 - Gut-lung cross talk in COVID-19 pathology and fatality rate -- 1. Introduction -- 2. Adult human gut microbiota -- 3. Respiratory tract microbiota -- 4. Gut-lung cross talk during viral COVID-19.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 5. Suggested COVID-19 intervention strategies through the use of probiotics and prebiotics -- 6. The role of probiotic in ventilator-associated pneumonia -- References -- 4 - Data sharing and privacy issues arising with COVID-19 data and applications -- 1. Introduction -- 2. The process of accelerating COVID-19 research -- 3. Medical data and sharing -- 3.1 Medical data acquiring -- 3.2 Medical data sharing -- 4. COVID-19 applications and privacy -- 4.1 Privacy metrics -- 4.2 Privacy metric selection method -- 4.3 Proposed method: privacy cost -- 4.3.1 Privacy algorithm -- 4.3.2 Privacy cost -- 5. Discussion and suggestions for further research -- References -- 5 - COVID-19 outlook in the United States of America: a data-driven thematic approach -- 1. Introduction -- 2. Sociotechnical theory -- 3. Methodology -- 3.1 Data collection -- 3.2 Data analysis -- 3.2.1 Sentiment analysis -- 3.2.2 Bag-of-words model (N-grams) -- 4. Results -- 5. Discussions -- 6. Conclusion -- References -- 6 - Artificial intelligence and COVID-19: fighting pandemics -- 1. Introduction -- 2. Phases for fighting pandemics -- 2.1 Phase I: mitigation or prevention -- 2.1.1 Enter artificial intelligence for pandemic prevention -- 2.2 Phase II: preparation -- 2.2.1 Enter artificial intelligence for pandemic preparation -- 2.3 Phase III: responding to or fighting pandemics -- 2.3.1 Enter artificial intelligence for fighting pandemics -- 2.4 Phase IV: recovery -- 2.4.1 Enter artificial intelligence for recovery -- 3. Present artificial intelligence efforts for fighting COVID-19 -- 3.1 Repositories and collections -- 3.2 Early warning systems -- 3.3 Intelligent diagnosis and preventing spread -- 3.4 Drug and vaccine discovery -- 4. Ethical use of artificial intelligence while fighting COVID-19 -- 5. Ongoing lessons from COVID-19 -- 6. Concluding remarks.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 6.1 Critical gaps in managing pandemics -- 6.2 Summary of core artificial intelligence activities for managing pandemics -- References -- 7 - Data science: a survey on the statistical analysis of the latest outbreak of the 2019 pandemic novel coronavirus diseas ... -- 1. Introduction -- 2. Background -- 2.1 Evolution of diseases from animals and their spread -- 2.2 COVID-19 epidemic to pandemic -- 2.3 Transmission phase -- 2.4 Precautions against COVID-19 -- 2.5 Statistical analysis-kick-start to data science -- 3. Overview of dataset -- 4. Statistical analysis -- 4.1 Two-way analysis: January 20, 2020 to March 19, 2020 -- 4.2 Variation analysis: January 20, 2020 to March 19, 2020 -- 4.3 One-way analysis: January 20, 2020 to April 25, 2020 -- 5. Outbreak of COVID-19, as of March 31, 2020 -- 6. Outbreak of COVID-19, as of April 25, 2020 -- 7. Comparison of COVID-19 in March and April -- 8. Conclusion -- References -- 8 - Application of big data in COVID-19 epidemic -- 1. Introduction -- 2. The growth of data in healthcare -- 2.1 Challenges of big data in COVID-19 -- 2.2 Importance of big data in COVID-19 -- 3. Big data privacy and ethical challenges in COVID-19 -- 4. Big data analytics in COVID-19 epidemic -- 5. Conclusion -- References -- 9 - Artificial intelligence-based solutions for COVID-19 -- 1. Introduction -- 1.1 Present and future COVID-19 contributions by artificial intelligence -- 1.1.1 Alerts and early signs -- 1.1.2 Tracking and prediction -- 1.1.3 Dashboards with info -- 1.1.4 Diagnosis and prognosis -- 1.1.5 Medication and cures -- 1.1.6 Social distancing -- 2. Technologic solutions to help combat the COVID-19 outbreak -- 2.1 Disease surveillance using artificial intelligence -- 2.2 Artificial intelligence-based CHATBOT and robot advisory services.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 2.3 Diagnostic artificial intelligence, facial recognition, and fever detector artificial intelligence -- 2.4 Intelligent drones and robots -- 2.5 Curative research artificial intelligence and information verification artificial intelligence -- 2.6 Sales prioritization using artificial intelligence and matching demand and supply -- 2.7 Artificial intelligence-based fast-developed testing kit -- 2.8 Smart quarantine information system and mobile phone technology data for contact tracing -- 2.9 Artificial intelligence for improving diagnosis efficiency and patient classification, and chest X-ray artificial intellige ... -- 2.10 Mobile apps for information sharing -- 2.11 Face Mask Detection System using artificial intelligence -- 2.12 Human Presence Detection System using facial recognition -- 2.13 Telemedicine solution for healthcare institutes -- 2.14 Machine learning social distancing application -- 3. Limitations and future scope -- 3.1 Conclusion -- References -- 10 - Telemedicine applications for pandemic diseases, with a focus on COVID-19 -- 1. Introduction -- 2. Telemedicine applications during epidemic/pandemic -- 3. Telemedicine applications for COVID-19 -- 3.1 Brazil -- 3.2 China -- 3.3 France -- 3.4 Germany -- 3.5 Spain -- 3.6 South Korea -- 3.7 The United Kingdom -- 3.8 The Unites States of America -- 3.9 Turkey -- 3.10 Other countries -- 4. Discussion -- 5. Conclusions and future work -- Acknowledgment -- References -- 11 - Impact of COVID-19 and lockdown policies on farming, food security, and agribusiness in West Africa -- 1. Introduction -- 2. Methods -- 2.1 Survey planning and data collection -- 2.2 Statistical analysis -- 3. Results -- 3.1 Characteristics of respondents -- 3.2 Farmers' rating of impact of COVID-19 and lockdown policies on their farm or business revenue.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 3.3 Impact of farmers' preparedness for COVID-19 and lockdown on their farm or business revenue.
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note Description based on publisher supplied metadata and other sources.
590 ## - LOCAL NOTE (RLIN)
Local note Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2022. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
655 #4 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Gupta, Deepak.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name de Albuquerque, Victor Hugo Costa.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Khanna, Ashish.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Print version:
Main entry heading Kose, Utku
Title Data Science for COVID-19
Place, publisher, and date of publication San Diego : Elsevier Science & Technology,c2021
International Standard Book Number 9780323907699
797 2# - LOCAL ADDED ENTRY--CORPORATE NAME (RLIN)
Corporate name or jurisdiction name as entry element ProQuest (Firm)
850 ## - HOLDING INSTITUTION
Holding institution
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://ebookcentral.proquest.com/lib/vajira-ebooks/detail.action?docID=6789182">https://ebookcentral.proquest.com/lib/vajira-ebooks/detail.action?docID=6789182</a>
Public note Click to View
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme National Library of Medicine Classification
Koha item type Electronic books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Barcode Date last seen Price effective from Koha item type
    National Library of Medicine Classification   Online Access Kuakarun Nursing Library Kuakarun Nursing Library Processing unit 24/05/2022   eb36177 24/05/2022 24/05/2022 Electronic books