Advanced AI and Internet of Health Things for Combating Pandemics / / edited by Mohamed Lahby, Virginia Pilloni, Jyoti Sekhar Banerjee, Mufti Mahmud

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
• Edizione: 1st ed. 2023.
• Descrizione fisica: 1 online resource (397 pages)
• Disciplina: 610.285
• Soggetto topico: Telecommunication; Medical informatics; Artificial intelligence; Medicine, Preventive; Health promotion; Communications Engineering, Networks; Health Informatics; Artificial Intelligence; Health Promotion and Disease Prevention
• Persona (resp. second.): LahbyMohamed
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Chapter 1 Knowledge Graphs for COVID-19: A Survey -- Chapter 2 Mapping effective practices and frameworks during the AEC industry’s combat with COVID-19: scientometric analysis -- Chapter 3 Deep Learning for Combating COVID-19 Pandemic in Internet of Medical Things (IoMT) Networks: A Comprehensive Review -- Chapter 4 Machine Learning Algorithms for Classification of COVID-19 using Chest X-Ray Images -- Chapter 5 Forecasting of COVID-19 cases Using AI and Real-time DataSet -- Chapter 6 Predicting Covid-19 Using Cough Audio Recordings -- Chapter 7 Computational Linguistics Techniques in Measuring Genetic Distance of Living Organisms -- Chapter 8 Explainable Artificial Intelligence (XAI) Based Analysis of Stress Among Tech Workers amidst COVID-19 Pandemic -- Chapter 9 COVID-19 Disease Segmentation using Deep Learning Techniques in CT Scan Images -- Chapter 10 Multimodal Diagnosis of COVID-19 Using Deep Wavelet Scattering Networks -- Chapter 11 Development of a Computer Aided Diagnosis System For Detection of COVID-19 Using Transfer Learning -- Chapter 12 COVID-19 Detection System in a Smart Hospital Setting using Transfer Learning and IoT-based Model -- Chapter 13 A Blockchain-based Secure Framework for Homomorphic AI in IoHT for Tackling COVID-19 Pandemic -- Chapter 14 Blockchain-Based Solution for Patient Controlled Health Records Sharing for Private Decentralized Storage -- Chapter 15 On Natural Language Processing to Attack COVID-19 Pandemic: Experiences of Vietnam -- Chapter 16 VacciNet: Towards a Reinforcement Learning based Smart Framework for Predicting the Distribution Chain Optimization of Vaccines for a Pandemic -- Chapter 17 AI-based logistics Solutions to tackle COVID-19 Pandemic and ensure a Sustainable financial Growth -- Chapter 18 A Comparative Modeling and Comprehensive Binding Site Analysis of the South African Beta COVID-19 Variant’s Spike Protein Structure.
• Sommario/riassunto: This book presents the latest research, theoretical methods, and novel applications in the field of Health 5.0. The authors focus on combating COVID-19 or other pandemics through facilitating various technological services. The authors discuss new models, practical solutions, and technological advances related to detecting and analyzing COVID-19 or other pandemic based on machine intelligence models and communication technologies. The aim of the coverage is to help decision-makers, managers, professionals, and researchers design new paradigms considering the unique opportunities associated with computational intelligence and Internet of Medical Things (IoMT). This book emphasizes the need to analyze all the information through studies and research carried out in the field of computational intelligence, communication networks, and presents the best solutions to combat COVID and other pandemics. Present discoveries in artificial intelligence techniques and machine learning and deep learning models for combating COVID-19; Provides an overview of practical and simulation concepts of Internet of Medical Things (IoMT) technologies; Proposes frameworks related to the detection and analysis of COVID-19 based on AI and IoMT; .
• Titolo autorizzato: Advanced AI and internet of health things for combating pandemics
• ISBN: 3-031-28631-6
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910735788203321
• Lo trovi qui: Univ. Federico II
• Serie: Internet of Things, Technology, Communications and Computing, . 2199-1081