1st Edition

Artificial Intelligence and Machine Learning An Intelligent Perspective of Emerging Technologies

    154 Pages 53 B/W Illustrations
    by CRC Press

    This book focuses on artificial intelligence (AI) and machine learning (ML) technologies and how they are progressively being incorporated into a wide range of products, including consumer gadgets, "smart" personal assistants, cutting-edge medical diagnostic systems, and quantum computing systems. This concise reference book offers a broad overview of the most important trends and discusses how these trends and technologies are being created and employed in the applications in which they are being used.

    Artificial Intelligence and Machine Learning: An Intelligent Perspective of Emerging Technologies offers a broad package involving the incubation of AI and ML with various emerging technologies such as Internet of Things (IoT), healthcare, smart cities, robotics, and more. The book discusses various data collection and data transformation techniques and also maps the legal and ethical issues of data-driven e-healthcare systems while covering possible ways to resolve them. The book explores different techniques on how AI can be used to create better virtual reality experiences and deals with the techniques and possible ways to merge the power of AI and IoT to create smart home appliances.

    With contributions from experts in the field, this reference book is useful to healthcare professionals, researchers, and students of industrial engineering, systems engineering, biomedical, computer science, electronics, and communications engineering.

    Chapter 1. Deep Learning Strategies in Biomedicine Imaging Technique

    P. Jayadharshini, Santhiya S, Keerthika S, and Priyanka S

    2. X-Ray-Based Pneumonia Detection Using ResNet50 and VGG16 Extracted Features and Conventional Machine Learning Algorithms

    Amit Virmani, Akhilesh Singh, Ritesh Agarwal, Sanjeet Kumar, and Hemant Kumar

    3. Enrichment of Human Life through Intelligent Wearable Technology

    Santhiya S, Jayadharshini P, Abinaya N, Sharmila C, Vasugi M, and Swetha Nallamangai K N

    4. Reliability and Validity of Survey Questionnaires for Identifying Learning Disabilities in an Intelligent Tutoring System

    Neelu Jyothi Ahuja, Sarthika Dutt, and Swati Arya

    5. A Survey of Artificial Intelligent Techniques for Cancer Detection

    Neha Nandal and Rohit Tanwar

    6. Ethical Issues in Medical Data

    Naga Durga Saile K and B. Venkatesh

    7. AI-Based Waste Classification in the Healthcare Industry

    Saswati Kumari Behera, Aouthithiye Barathwaj SR Y, Vasundhara L, Saisudha G, and Haariharan N C

    8. SmartWear: An IoT-Based Integration of Home Automation and Healthcare Watch

    Saswati Kumari Behera, Saisudha G, and Vasundhara L

    9. An Analytical Comparison of the Identification of Non-Small Cell Lung Cancer Nodules Using CT Scans and Prominent Deep Learning Models

    Sunil Kumar, Vishal Awasthi, Amar Pal Yadav, Shivneet Tripathi, and Prachi Chhabra

    10. Abnormality Classifications Using Machine Learning

    Anupam Singh, Ravendra Singh, and Nitin Arora

    11. Multilayer Perceptron-Based Speech Emotion Recognition for Identifying the Problematic Skills of Dyslexic Learners

    Sarthika Dutt, Rohit Kanauzia, Aditi, and Himanshu Bartwal

    12. An Improved Convolutional Neural Network-Based Detection Framework for COVID-19 Omicron and Delta Variants Employing CT Scans

    Sunil Kumar, Abhishek Dwivedi, Shekhar Verma, and Abhishek Kumar Mishra

    13. A Survey of IoT in Healthcare: Technologies, Applications, and Challenges

    S. Subashini, G.K. Kamalam, and P. Vanitha


    Rohit Tanwar, PhD, is an Associate Professor in the School of Computer Science at the University of Petroleum and Energy Studies (UPES), Dehradun, Misraspatti, India.

    Surbhi Bhatia Khan, PhD, a Lecturer in the Department of Data Science, School of Science, Engineering and Environment, University of Salford, Manchester, United Kingdom.

    Varun Sapra, PhD, is presently associated with the School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India. Before joining academia, he was in the corporate sector and worked at Cupid Software, Web Opac Applications, CMA, and many more.

    Neelu Jyothi Ahuja, PhD, is a Professor and Head of the Department of Systemics at the School of Computer Science at the University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.