1st Edition
Internet of Things enabled Machine Learning for Biomedical Application
The text begins by highlighting the benefits of the internet of things enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and examines security and privacy issues in the healthcare systems using the internet of things. The text elaborates on image processing implementation for medical images to detect and classify diseases based on magnetic resonance imaging and ultrasound images.
This book:
· Covers the procedure to recognize emotions using image processing and the internet of things-enabled machine learning.
· Highlights security and privacy issues in the healthcare system using the internet of things.
· Discusses classification and implementation techniques of image segmentation.
· Explains different algorithms of machine learning for image processing in a comprehensive manner.
· Provides computational intelligence on the internet of things for future biomedical applications including lung cancer.
It is primarily written for graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and biomedical engineering.
Chapter 1: ML and IoT coupled Bio-Medical applications in Healthcare: Smart Growth and Upcoming Challenges
Vasanth R, Paranthaman M, Sivaprakash P
Chapter 2: Recent Advances in Ubiquitous Sustainable Healthcare Systems
Shwetha Baliga, Pushkar R Kulkarni
Chapter 3: IoT enabled Healthcare System using Machine Learning
Ms. P.Jothi Thilaga, Mr. K. Vignesh Saravanan, Dr. S. Kavi Priya, Dr. K. Vijayalakshmi
Chapter 4: An Efficient Architecture for Classification of Super Resolution Enhanced Human Chromosome Images
Dr. D. Menaka, Ms. K. S. Subhashini
Chapter 5: Applications of Machine Learning to the Impact of IoT in Biomedical Applications
Shwetha Baliga, Rakshita Basarakod, Kalathmika G, Nandana P Pillai, Jayashree Shivakumar, Preeti Yadav
Chapter 6: Ovarian Cancer Detection Using IoT-Based Intelligent Assistant and Blockchain Technology
Mohsen Ghorbian, Saeid Ghorbian
Chapter 7: Blood oxygen level and pulse rate measurement using hemodialysis using IoT and Computational Intelligence
Ms. N. Vigneshwari, Dr. C. Sivamani, Dr. S. Selvi, Dr. G. Revathy
Chapter 8: Dental Shade Matching using machine Learning Models
Shishira R, S Deepthi Nayak, Geetishree Mishra, M N Suma
Chapter 9: Brain Tumor Detection for Recognising Critical Brain Damage in Patients Using Computer Vision
Vivek Veeraiah, Parth Sharma, Kumud Saxena, Niraj Kumar Sahu, Khushboo Sharma, Jay Kumar Pandey, Dr. R. K. Yadav, Dr. Mrityunjai Rai
Chapter 10: Smart Therapist: The Mental Health detector
Arunabha Dutt, Nizar Banu P K, Akarshi Bansal, Krishna Bansal
Chapter 11: Medical Image Analysis based on Deep Learning Approach and Internet of Medical Things (IoMT) for early Diagnosis of Retinal disease
S.Karkuzhali, Thendal Puyalnethi, Senthilkumar S
Chapter 12: Intelligent E-Learning Platform Consolidating Web of Things and Chat-GPT
Neha Katiyar, Mayank Deep Khare, Jatin Kumar, Ayush sharma, Sachin Rawat, Jyoti Srivastava
Chapter 13: Issues and Challenges in security and privacy with E-health care: a thorough literature analysis
Manikandan A, Sanjay T, Gautam Menon, Aswin R, Parthiv Bijumon Bhaskar, Mahadev Govind R, Ramprasad O G
Chapter 14: Harnessing the Power of Distributed Cloud and Edge Computing for Advanced Healthcare Systems
Sampath Boopathi
Chapter 15: Securing Cloud-Based IoT: Exploring the Significance of Lightweight Cryptography for Enhanced Security
Gaikwad Vidya S, Nilesh P. Sable, Disha S. Wankhede, Vaishali Mishra, Madhuri P. Karnik, Nitin Ambhore, Akshay Manikjade
Chapter 16: Security and Privacy in the Internet of Medical Things (IoMT)-Based Healthcare: Ensuring Trust and Safety
Deepali Vashistha, Dhairya Mehta, Pranav Vashistha, Pranjal Mairal, Malaram Kumhar, Jitendra Bhatia
Chapter 17: A Comprehensive Study of the Problem and Challenges Associated with Machine Learning Enabled IOT in Biomedical Applications
Sandeep Bhatia, Amit Kumar Goel, Basetty Mallikarjun, Bharat Bhushan Naib, Neha Goel, Soniya Verma
CHAPTER 18: A Machine Learning-enabled Internet of Things Model for Cloud-based Biomedical Applications
Palanivel Kuppusamy, Nandhu Palanivel, Suresh Joseph K
Chapter 19: Machine Learning Enabled IoT for Biomedical applications: Problem and challenges
Hashmat Usmani, Renu Rani
Chapter 20: IOT driven Machine learning mechanisms for Healthcare Applications
Dr. Gopala Krishnan Karuppaiah, Dr. Karthikeyan Velayuthapandian, Mr. Sridhar Raj Sankara Vadivel
Biography
Dr. Neha Goel is working as Associate Professor in the department of Electronics & Communication Engineering at RKGIT, Ghaziabad. She has completed her PhD from SRM University, Chennai in 2019. She has 18 years of rich experience in teaching. Her area of interest on VLSI design, CMOS design, Internet of things, Machine learning. She has guided several Beach Projects and has published 38 papers in various National/International journals and conferences. She has been granted and has published 3 patents. She has also attended various workshops and seminars in various fields.
Dr. Ravindra Kumar Yadav is a Professor and Head of the Department of Electronics & Communication Engineering at RKGIT, Ghaziabad. He has a B.E, M.E., and PhD in the field of Electronics & Communication engineering. He has 26 years of rich experience in teaching, research and development activities, administration and managing and upbringing of higher educational institutions. He has guided several B. Tech and M. Tech projects and is also guiding PhD students from IIT Dhanbad as a co guide. He has published 90 papers to his credit in international/national journals, conferences, and symposiums. Prof. Yadav is a Reviewer for several National/International Journals of high reputation. He has chaired/participated technical sessions at multiple international and national conferences/ seminars held throughout the country.
