Novel AI and data science advancements for sustainability in the era of COVID-19

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Chang, Victor, Abdel-Basset, Mohamed, Ramachandran, Muthu, Green, Nicolas, Wills, Gary
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Academic Press, 2022.
Temas:
Since 2020
Artificial intelligence.
COVID-19 Pandemic, 2020- > Data processing.
Big data.
Artificial Intelligence
Intelligence artificielle.
Pand�emie de COVID-19, 2020- > Informatique.
Donn�ees volumineuses.
artificial intelligence.
Artificial intelligence
Big data
Electronic data processing
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19
  • Copyright
  • Contents
  • Contributors
  • Chapter 1: Deep learning-based hybrid models for prediction of COVID-19 using chest X-ray
  • 1. Introduction
  • 2. Related work
  • 3. Modeling
  • 3.1. PCA-feature ensembles
  • 3.2. Optimally weighted majority voting
  • 3.3. Feature extraction
  • 3.4. Layer modification
  • 4. Experimental setup
  • 4.1. Baseline models
  • 4.1.1. VGG-16 (Simonyan & Zisserman, 2015)
  • 4.1.2. ResNet 50 (He et al., 2016)
  • 4.1.3. Inception V3 (Szegedy et al., 2015)
  • 4.2. Dataset
  • 4.3. Data augmentation
  • 4.4. Other preprocessing
  • 4.5. Evaluation metrics
  • 4.5.1. Accuracy
  • 4.5.2. Precision
  • 4.5.3. Recall
  • 4.5.4. F-1 score
  • 4.6. Experimental details
  • 5. Results and discussion
  • 6. Conclusions
  • References
  • Chapter 2: Investigation of COVID-19 and scientific analysis big data analytics with the help of machine learning
  • 1. Introduction and background
  • 2. Literature review
  • 3. COVID-19 pandemic in the new era of big data analytics: Methodological innovations and future research directions
  • 3.1. Deep learning applications for COVID-19
  • 3.2. Big data analytics as a tool for fighting pandemics: A systematic review of literature
  • 4. Review of big data analytics, artificial intelligence and nature-inspired computing models towards accurate detection ...
  • 5. Significant applications of big data in COVID-19 pandemic
  • 6. Research problem
  • 7. Research questions
  • 8. Objectives
  • 9. Methodology
  • 9.1. Techniques
  • 10. Algorithm
  • 11. Conclusion
  • 11.1. Big data
  • 11.2. Machine learning
  • 11.3. COVID-19
  • Acknowledgment
  • References
  • Chapter 3: Designing a conceptual model in the artificial intelligence environment for the health care sector
  • 1. Introduction
  • 2. Background
  • 3. Literature review
  • 4. Approach suggested for designing a conceptual model
  • 5. Selection of concepts in information and communication technology
  • 5.1. Artificial intelligence
  • 5.2. Role of artificial intelligence
  • 5.3. Machine learning
  • 5.4. Algorithms
  • 5.5. Data warehouse
  • 5.6. Virtual reality
  • 5.7. Cloud computing
  • 6. Databases related to classification of diseases, digital image code, and viruses taxonomy
  • 6.1. International Classification of Diseases (ICD)
  • 6.2. Digital Imaging and Communications in Medicine (DICOM)
  • 6.3. International Committee on the Taxonomy of Viruses (ICTV)
  • 7. Role of core team
  • 7.1. Medical research activities
  • 7.2. Virtual medical research center
  • 8. Overview of viruses
  • 8.1. Viruses
  • 8.2. Spreading vectors
  • 8.3. Human immunodeficiency viruses
  • 8.4. Role of immune system
  • 8.5. Parts of immune system
  • 8.6. Characteristics of immune system
  • 8.6.1. White blood cells
  • 8.6.2. Antibodies
  • 8.6.3. Complement system
  • 8.6.4. Lymphatic system

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