About the Book
The Internet of Medical Things (IoMT) is a system that collects data from patients with the help of different sensory inputs, e.g., an accelerometer, electrocardiography, and electroencephalography. This text presents both theoretical and practical concepts related to the application of machine learning and Internet of Things (IoT) algorithms in analyzing data generated through healthcare systems.
Illustrates the latest technologies in the healthcare domain and the Internet of Things infrastructure for storing smart electronic health records
Focuses on the importance of machine learning algorithms and the significance of Internet of Things infrastructure for healthcare systems
Showcases the application of fog computing architecture and edge computing in novel aspects of modern healthcare services
Discusses unsupervised genetic algorithm-based automatic heart disease prediction
Covers Internet of Things–based hardware mechanisms and machine learning algorithms to predict the stress level of patients
The text is primarily written for graduate students and academic researchers in the fields of computer science and engineering, biomedical engineering, electrical engineering, and information technology.
Table of Contents:
1. Applications of Internet of Things and Machine Learning Technologies in Healthcare 2. Automated Detection of Patients Developing Anorexia Nervosa and Bulimia Nervosa using XGBoost Algorithm 3. Breast Cancer Prediction using Machine Learning Approach 4. A Survey on the Development of Deep Learning based Techniques in the Diagnosis of Parkinson's disease 5. A deep learning-based approach for detecting diabetic retinopathy in retina images 6. Optimized CNN for CBIR in Medical Imageset 7. Paddy Leaf Diseases Detection using Otsu and Yen Thresholding with Deep Convolutional Neural Network 8. Applications of IoT Enabled Systems in Healthcare Industry 9. Enhancing Health and Environmental Monitoring: Open Source IoT-Enabled SCADA system with Node-Red, InfluxDB, Grafana, and Raspberry Pi 10. Transfer learning for healthcare 11. Conclusion
About the Author :
Dr Prasenjit Dey received his B.Tech. degree in computer science and engineering from the West Bengal University of Technology, Kolkata, India, in 2010, and the M.Tech. degree in computer science and engineering from the National Institute of Technology Durgapur, Durgapur, India, in 2012. He was an Associate Innovator with Nivio Technologies, Gurgaon, India, in 2012. He was hardware graphics designer at Intel from 2017 to 2018. He received his Ph.D. degree in computer science and engineering from the National Institute of Technology Durgapur, Durgapur, India, in 2018. He has joined the Cooch Behar Government Engineering College, Cooch Behar, India in 2018 and is currently working as an Assistant Professor in the Department of Computer Science. His current research interests include artificial neural networks, pattern recognition and machine learning. He has more than 10 research publications in internationally reputed journals, international edited books, and international IEEE conference proceedings. He served as a reviewer in several International conferences and also in several international editorial books. He also served as a reviewer in some reputed international journals, like, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Systems, Man, and Cybernetics, IEEE Transactions on Artificial Intelligence, Applied Soft Computing, Elsevier, etc. He has been the member of the organizing and technical program committees of several national and international conferences. He has been invited to different seminars as an expert speaker.
Dr. Sourav De did his Bachelors in Information Technology from The University of Burdwan, Burdwan, India in 2002. He did his Masters in Information Technology from West Bengal University of Technology, Kolkata, India in 2005. He completed PhD in Computer Science and Technology from Indian Institute of Engineering & Technology, Shibpur, Howrah, India in 2015. He is currently an Associate Professor of Computer Science & Engineering Department in Cooch Behar Government Engineering College, West Bengal from the year 2016. Previous to this, he was an Assistant Professor for more than ten years in the Department of Computer Science and Engineering and Information Technology of University Institute of Technology, The University of Burdwan, Burdwan, India. He served as a Junior Programmer in Apices Consultancy Private Limited, Kolkata, India in 2005. He is a co-author of one book and the co-editor of sixteen books and has more than 69 research publications in internationally reputed journals, international edited books, and international IEEE conference proceedings and five patents and three copyright to his credit. He served as a reviewer in several International IEEE conferences and also in several international editorial books. He also served as a reviewer in some reputed international journals, like, Applied Soft Computing, Elsevier, B. V., Knowledge-Based Systems, Soft Computing Letters, Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization, Inderscience Journals, etc. He has been the member of the organizing and technical program committees of several national and international conferences. He has been invited to different seminars as an expert speaker. His research interests include soft computing, pattern recognition, image processing, and data mining. Dr. De is a Senior member of IEEE and also member of ACM, Institute of Engineers (IEI), Computer Science Teachers Association (CSTA), Institute of Engineers and IAENG, Hong Kong. He is a life member of ISTE, India.
Dr. Sudip Kumar Adhikari passed B. Tech in Computer Science & Engineering from Vidyasagar University. He obtained the M.E. and Ph.D. degree in Computer Science & Engineering from Jadavpur University. He had more than 18 years of teaching experiences. He is currently an assistant professor in Computer Science & Engineering Department of Cooch Behar Government Engineering College, Cooch Behar, India. He had published more than eighteen research papers in reputed International Journals and Conferences. His research interest includes Medical image processing, Pattern recognition, Artificial intelligence, Soft Computing. He is a Senior Member of IEEE and member of Institute of Engineers. He served as a reviewer in several International conferences and also in several reputed international journals like, Applied Soft Computing, Elsevier, IET Computer Vision, IEEE Access, and IEEE Transaction on Fuzzy System etc. He has been the member of the organizing and technical program committees of several national and international conferences. He has been invited to different seminars as an expert speaker.
Mr. Indrajit Kar holds a Master's degree in Computational Biology and a Bachelor's in Science from a Bengaluru university. A dynamic entrepreneur, He has built teams at Siemens, Accenture, IBM, and Infinite Data Systems. He's now the AVP and Global Head of AI and ML at Zensar Technologies, overseeing ZAIR and Data Practices. He has authored 21 research papers published in IEEE, Springer, Wiley, and CRC, covering topics like Large Language Models, Computer Vision, NLP, and Time Series analysis. He has received five "Best Paper Awards," including one from Cardiff University. A mentor to startups, he's guided two to revenue generation and has received numerous accolades, including the '40 Under 40 Data Scientists' award from Analytics India Magazine. His trophy case includes two IP Samman and Service Excellence awards from Siemens, the Growth Market Award from Accenture, and various innovation and contribution awards from Accenture, IBM, Siemens Healthcare, and Hewlett-Packard. He has managed over 30 projects in AI/ML and is an accomplished author, co-writing two books, one on Generative AI, and has delivered 19 lectures and keynote speeches. An Adjunct Faculty member for a Data Science course at Upgard, he holds 14 AI/ML patents. Under his leadership, his teams have won five Best Team/Project awards, including Best AI/ML Project House and the Werner Von Siemens award. His initiatives have led Siemens to be ranked as a top Data Science company by Analytics India Magazine. He has mentored over 150 AI and ML aspirants and has been a speaker at universities such as IIT Madras and PESIT, contributing to the field's growth and innovation.
