Artificial intelligence in medical virology / Jyotir Moy Chatterjee, Shailendra K. Saxena, editors.
Moy Chatterjee, Jyotir, editor.; Saxena, Shailendra K., 1950- editor.
2023
QR201.V55 A78 2023
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title Artificial intelligence in medical virology / Jyotir Moy Chatterjee, Shailendra K. Saxena, editors.
ISBN 9789819903696 electronic book
9819903696 electronic book
9819903688
9789819903689
DOI https://doi.org/10.1007/978-981-99-0369-6
Published Singapore : Springer, 2023.
Language English
Description 1 online resource (189 pages) : illustrations (black and white).
Other Standard Identifiers 10.1007/978-981-99-0369-6 doi
Call Number QR201.V55 A78 2023
Dewey Decimal Classification 616.9/101028563
Summary This book comprehensively reviews the potential of Artificial Intelligence (AI) in biomedical research and healthcare, with a major emphasis on virology. The initial chapter presents the applications of machine learning methods for structured data, such as the classical support vector machine and neural network, modern deep learning, and natural language processing for unstructured data in biomedical research and healthcare. The subsequent chapters explore the applications of AI in tackling COVID-19, analysis of the pandemic, viral infection, disease spread, and control. The book further identifies the potential applications of machine learning in the field of virology with a focus on the key aspects of infection: diagnosis, transmission, response to treatment, and resistance. The book also discusses progress and challenges in developing viral vaccines and examines the application of viruses in translational research and human healthcare. Furthermore, the book covers the applications of artificial intelligence-mediated diagnosis and the development of drugs to treat the disease. Towards the end, the book summarizes the ethical and legal challenges posed by AI in healthcare and biomedical research. This book is an invaluable source for researchers, medical and industry practitioners, academicians, and students exploring the applications of AI in biomedical research and healthcare.
Access Note Access limited to authorized users.
Source of Description Description based on print version record.
Added Author Moy Chatterjee, Jyotir, editor.
Saxena, Shailendra K., 1950- editor.
Series Medical virology (Springer (Firm))
Available in Other Form ARTIFICIAL INTELLIGENCE IN MEDICAL VIROLOGY.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
Chapter 1. Artificial Intelligence for Global Healthcare
Chapter 2. Artificial Intelligence for Epidemiology COVID-19: Quick Assessment
Chapter 3. Artificial Intelligence in rural health in developing countries
Chapter 4. THE ROLE OF ARTIFICIAL INTELLIGENCE TO TRACK COVID-19 DISEASE
Chapter 5. Artificial Intelligence Techniques based on K-Means two way Clustering and Greedy Triclustering approach for 3D Gene Expression Data (GED)
Chapter 6. Detection of COVID-19 cases from X-Ray and CT Images using Transfer Learning & Deep Convolution Neural Networks
Chapter 7. Computer Vision: Augmented Reality (AR), Virtual Reality (VR), Telehealth and Digital Radiology
Chapter 8. STROKE DISEASE PREDICTION MODEL USING ANOVA WITH CLASSIFICATION ALGORITHMS
Chapter 9. A CONCISE REVIEW ON DEVELOPMENTAL AND EVALUATION METHODS OF ARTIFICIAL INTELLIGENCE ON COVID 19 DETECTION
Chapter 10. Artificial Intelligence based Healthcare Industry 4.0 for Disease Detection using Machine Learning Techniques
Chapter 11. Deep Autoencoder Neural Networks for Heart Sound Classification.

Browse Subjects

Show more subjects...

Statistics

from
to
Export