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Data Science for COVID-19 : Volume 2: Societal and Medical Perspectives.

By: Contributor(s): Material type: TextTextPublisher: San Diego : Elsevier Science & Technology, 2021Copyright date: �2022Description: 1 online resource (814 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780323907705
Genre/Form: Additional physical formats: Print version:: Data Science for COVID-19DDC classification:
  • 614.592414
Online resources:
Contents:
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.
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.
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.
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.
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.
3.3 Impact of farmers' preparedness for COVID-19 and lockdown on their farm or business revenue.
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Item type Current library Shelving location Call number Status Date due Barcode Item holds
Electronic Book Electronic Book Kuakarun Nursing Library Processing unit Online Access eb36177
Total holds: 0

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.

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.

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.

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.

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.

3.3 Impact of farmers' preparedness for COVID-19 and lockdown on their farm or business revenue.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2022. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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