1st Edition

Emerging Technologies for Combatting Pandemics AI, IoMT, and Analytics

    310 Pages 17 Color & 70 B/W Illustrations
    by Auerbach Publications

    310 Pages 17 Color & 70 B/W Illustrations
    by Auerbach Publications

    The COVID-19 pandemic has significantly affected the healthcare sector across the globe. Artificial Intelligence (AI) and the Internet of Medical Things (IoMT) play important roles when dealing with emerging challenges. These technologies are being applied to problems involving the early detection of infections, fast contact tracing, decision-making models, risk profiling of cohorts, and remote treatment. Applying these technologies runs against challenges including interoperability, lack of unified structure for eHealth, and data privacy and security. Emerging Technologies for Combatting Pandemics: AI, IoMT, and Analytics examines multiple models and solutions for various settings including individual, home, work, and society. The world’s healthcare systems are battling the novel coronavirus, and government authorities, scientists, medical practitioners, and medical services are striving hard to surmount these challenges.

    This book focuses on the design and implementation of AI-based approaches in the proposed COVID-19 solutions that are enabled and supported by IoMT, sensor networks, cloud and edge computing, robotics, and analytics. It covers technologies under the umbrella of AI that include data science, big data, machine learning (ML), semantic technologies, analytics, and cyber security.

    Highlights of the book include:

    • Epidemic forecasting models
    • Surveillance and tracking systems
    • IoMT and Internet of Healthcare Things-based integrated systems for COVID-19
    • Social network analysis systems
    • Radiological image- based diagnosis systems
    • Computational intelligence methods

    This reference work is beneficial for interdisciplinary students, researchers, and healthcare and technology professionals who need to know how computational intelligence could be used for surveillance, control, prevention, prediction, diagnosis, and potential treatment of the disease.

    Foreword

    Preface

    Acknowledgments

    About the Editors

    List of Contributors

    1 Artificial Intelligence Leveraged Internet of Medical Things and Continuous Health Monitoring and Combating Pandemics within the Internet of Medical Things Framework

    CHITHARANJAN BILLA AND MURTHY CHAVALI

    2 Assessing the Economic Impact of COVID-19

    SONIA SHARMA, ANSHI GUPTA, AND JAGADEESH CHANDRA BOSE K.

    3 Assessing the Economic Impact of COVID-19 on the Implications of the Internet of Things Adoption on Small and Medium Enterprise Business’s Sustainability

    R. ABD SHUKOR AND W. K. MOOI

    4 Impact of COVID-19: Insights from Key Sectors of the Indian Economy

    REENA MALIK

    5 Future Scope of Artificial Intelligence in Healthcare for COVID-19

    MANAS KUMAR YOGI AND JYOTSNA GARIKIPATI

    6 Patient Recovery and Tracing Repercussions for COVID-19 in Discharged Patients

    B. PATEL, K. PATEL, D. PATEL, M. BOHARA, AND A. GANATRA

    7 The Impact of COVID-19 on the Maritime Economy: A Study on Bangladesh

    BORNALI RAHMAN, MOHAMMAD TAMEEM HOSSAIN AZMI, AND JAKIR HOSAIN

    8 Intelligent Optimization and Computational Learning Techniques for Mitigating Pandemics

    KAYODE ABIODUN OLADAPO, JIDE EBENEZER TAIWO AKINSOLA, MORUF ADEAGBO, FATHIA ONIPEDE, SAMUEL AYOMIKUN AKINSEINDE, AND ADEBOLA ABDULWAHEED YUSUF

    9 Various Deep Learning Methodologies for COVID-19 Diagnosis

    K. PATEL, B. PATEL, M. BOHARA, D. PATEL, AND A. GANATRA

    10 Hybridization of Decision Tree Algorithm Using Sequencing Predictive Model for COVID-19

    A. A. AWOSEYI, JIDE EBENEZER TAIWO AKINSOLA, O. M. OLADOJA, MORUF ADEAGBO, AND O. O. ADEBOWALE

    11 CoVICU: A Smart Model for Predicting the Intensive Care Unit Stay of COVID-19 Patients Using Machine Learning Techniques

    SAKTHI JAYA SUNDAR RAJASEKAR, V. ARUNA DEVI, AND VARALAKSHMI PERUMAL

    12 Long Short-Term Memory-Based Recurrent Neural Network Model for COVID-19 Prediction in Different States of India

    MREDULRAJ S. PANDIANCHERY, V. SOWMYA, E. A. GOPALAKRISHNAN, AND K. P. SOMAN

    13 Dengue in the Presence of COVID-19: Evaluation of Tree-Based Classifiers Using Stratified K- Fold on Dengue Dataset

    SUPREET KAUR AND SANDEEP SHARMA

    Index

    Biography

    Dr. M. Rubaiyat Hossain Mondal is a Professor in the Institute of Information and Communication Technology (IICT) at Bangladesh University of Engineering and Technology (BUET), Bangladesh.

    Dr. Utku Kose is an Associate Professor in Suleyman Demirel University, Turkey.

    Dr. Surya Prasath is a mathematician with expertise in the application areas of image processing and computer vision.

    Dr. Prajoy Podder is a researcher at the Institute of Information and Communication Technology, Bangladesh University of Engineering and Technology.

    Dr. Subrato Bharati is a researcher at the Institute of Information and Communication Technology, Bangladesh University of Engineering and Technology.

    Dr. Joarder Kamruzzaman is a Professor at the School of Engineering, Information Technology and Physical Sciences, Federation University, Australia.