1st Edition

Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering

    320 Pages 65 B/W Illustrations
    by CRC Press

    This book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers around the world.

    Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering discusses IoT and ML devices that are deployed for enabling patient health tracking, various emergency issues, and the smart administration of patients. It looks at the problems of cardiac analysis in e-healthcare, explores the employment of smart devices aimed for different patient issues, and examines the usage of Arduino kits where the data can be transferred to cloud for internet-based uses. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. The authors also examine the role of IoT and ML in electroencephalography (EEG) and magnetic resonance imaging (MRI), which play significant roles in biomedical applications. This book also incorporates the use of IoT and ML applications for smart wheelchairs, telemedicine, GPS positioning of heart patients, and smart administration with drug tracking. Finally, the book also presents the application of these technologies in the development of advanced healthcare frameworks.

    This book will be beneficial for new researchers and practitioners working in the biomedical and healthcare fields. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practices of medical image retrieval, and brain image segmentation.

    1. Applications of Artificial Intelligence and Internet of Things in
    Healthcare Industries. 
    A. Ameer Rashed Khan, Muhammad Ilyas R N, and M. Nagoor Meeral
    2. ML for Internet of Medical Things Applications: Framework, Developments, and Challenges. 
    Divneet Kaur, Bharatdeep Singh, and Sita Rani
    3. IoT Healthcare's Advanced Decision Support through Computational Intelligence. 
    Pawan Whig, Jhansi Bharathi Madavarapu, Nikhitha Yathiraju, and Ramya Thatikonda
    4. Insights into Thyroid Disease: Harnessing Machine Learning for Analysis and Classification of Multi-Label Medical Data. 
    Shalu Surendran and Umme Salma M.
    5. Longitudinal Study on Non-Communicable Diseases Using Machine Learning. 
    Joshua K Deepak and Umme Salma M
    6. Uncovering Machine Learning Trends in Biomedical: Pulmonary Disease Diagnosis. 
    Anish Singh, Atul Kabra, and Anupam Bonkra
    7. Smart Surgery: Navigating Precision through Machine Learning and IoT. 
    Anita Mohanty, Ambarish G. Mohapatra, and Subrat Kumar Mohanty
    8. Classification and Detection of Brain Tumors in MRI Images Using Machine Learning Techniques. 
    Ganesh Khekare, Gaurav Kumar Ameta, Rahul Sharma, Anil Turukmane, Pooja Sharma, Urvashi Khekare, and Rahul Agrawal
    9. Advanced Deep Learning for Early Alzheimer's Detection: A Comparative Analysis. 
    Deepika Roselind Johnson, Logeswari G, and Sudhakaran G
    10. Artificial Intelligence and Machine Learning in Biomedical Signal Processing. 
    Aditya Kumar, Niharika Koch, Sk Imran, and Jainath Yadav
    11. Machine Learning and Internet of Things Biomedical Technologies. 
    Ruchin Kacker, Sanjay Kumar Singh, and Amit Arora
    12. Revolutionizing Chronic Kidney Disease Prediction: An Enhanced Semi-Supervised Learning Model. 
    G.Logeswari, J.Deepika Roselind, and G. Sudhakaran 
    13. Analysing the Seamless Integration of Machine Learning and Internet of Things in the Daily Dynamics of Contemporary Living. 
    Kanchan Naithani, Y. P. Raiwani, and Shrikant Tiwari
    14. Convergence of AR, VR, IoT with Artificial Intelligence to train Surgeons for Medical Surgeries. 
    Rishabh Jha, Amrita Singh, and Arun Kumar Rana
    15. An overview of IoT & Machine Learning Approach in Health Care. 
    Niva Tripathy, Subhranshu Sekhar Tripathy, and Subhendu Kumar Pani
    16. Healthcare Unbound: Navigating Emerging Trends and Future Applications in IoT-Based Innovations for Daily Well-being.. 
    Mrunalini H Kulkarni and Poonam R Inamdar
    17. Image Guided Surgery Through ML and IOT. 
    Pallavi Pandey and Priyanka Gauniya


    Dr. Arun Kumar Rana is currently an Assistant Professor-3 in Galgotias College of Engineering and Technology, Greater Noida, India with more than 16 years of experience. His area of interest includes Image Processing, Wireless Sensor Network, Internet of Things, AI, and Machine Learning and Embedded systems.

    Dr Vishnu Sharma is a Professor and Dean CSE at ITS College of Engineering,  Greater Noida India. Dr. Vishnu Sharma completed his B.Tech, M.Tech, and Ph.D. (CSE) in 2012 from Gov. Autonomous Institute, Madhav Institute of Technology & Science (M.I.T.S.) Gwalior (M.P.) in Computer Science & Engineering and Affiliated to Rajiv Gandhi Technical University, Bhopal, India. His areas of interest are mobile computing, cybersecurity, and advanced mobile computing.

    Dr. Sanjeev Kumar Rana is a Professor of Computer Science and Engineering at Maharishi Markandeshwar (deemed to be university), Mullana-Ambala, India. He earned his PhD degree from Maharishi Markandeshwar University, Mullana-Ambala, India in 2012. He is also a CISCO certified instructor. His research interest includes distributed computing, network security, blockchain technology, big data analytics.

    Vijay Shanker Chaudhary is an Associate Professor (GCET, Greater Noida) and Researcher (Photonic Crystal Fiber Based Biosensors), He received his PhD degree from the Madan Mohan Malviya University of Technology, Gorakhpur, India. His research interests include photonic crystal fiber, optical fiber sensors, and terahertz sensing properties.