LEADER 04431nam 22006135 450 001 9910717428303321 005 20251008152028.0 010 $a981-9903-69-6 024 7 $a10.1007/978-981-99-0369-6 035 $a(CKB)5580000000533222 035 $a(DE-He213)978-981-99-0369-6 035 $a(MiAaPQ)EBC7240879 035 $a(Au-PeEL)EBL7240879 035 $a(PPN)269658408 035 $a(MiAaPQ)EBC7239595 035 $a(EXLCZ)995580000000533222 100 $a20230421d2023 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence in Medical Virology /$fedited by Jyotir Moy Chatterjee, Shailendra K. Saxena 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2023. 215 $a1 online resource (XVI, 189 p. 1 illus.) 225 1 $aMedical Virology: From Pathogenesis to Disease Control,$x2662-9828 311 08$a981-9903-68-8 320 $aIncludes bibliographical references. 327 $aChapter 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. 330 $aThis book comprehensively reviews the potential of Artificial Intelligence (AI) in biomedical research and healthcare, with a major emphasis on virology. The initial chapter presents the applications of machine learning methods for structured data, such as the classical support vector machine and neural network, modern deep learning, and natural language processing for unstructured data in biomedical research and healthcare. The subsequent chapters explore the applications of AI in tackling COVID-19, analysis of the pandemic, viral infection, disease spread, and control. The book further identifies the potential applications of machine learning in the field of virology with a focus on the key aspects of infection: diagnosis, transmission, response to treatment, and resistance. The book also discusses progress and challenges in developing viral vaccines and examines the application of viruses in translational research and human healthcare. Furthermore, the book covers the applications of artificial intelligence-mediated diagnosis and the development of drugs to treat the disease. Towards the end, the book summarizes the ethical and legal challenges posed by AI in healthcare and biomedical research. This book is an invaluable source for researchers, medical and industry practitioners, academicians, and students exploring the applications of AI in biomedical research and healthcare. 410 0$aMedical Virology: From Pathogenesis to Disease Control,$x2662-9828 606 $aVirology 606 $aDiseases$xCauses and theories of causation 606 $aArtificial intelligence 606 $aVirology 606 $aPathogenesis 606 $aArtificial Intelligence 615 0$aVirology. 615 0$aDiseases$xCauses and theories of causation. 615 0$aArtificial intelligence. 615 14$aVirology. 615 24$aPathogenesis. 615 24$aArtificial Intelligence. 676 $a060 702 $aMoy Chatterjee$b Jyotir 702 $aSaxena$b Shailendra K. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910717428303321 996 $aArtificial Intelligence in Medical Virology$93355627 997 $aUNINA