Artificial Intelligence in e-health Framework, Volume One: AI, Classification, Wearable Devices, and Computer-Aided Diagnosis presents a variety of AI techniques and applications for solving issues in the healthcare industry. As Artificial Intelligence is increasingly incorporated into medical systems and methods, it is critical to understand the formulations and basics of machine and deep learning as well as how to implement these advances into practice. This book specifically explores Artificial Intelligence developments in disease diagnosis, health monitoring, medical image recognition, and diagnostics, as well as e-health records management.
This is a valuable resource for health professionals, scientists, researchers, students, and all who wish to broaden their knowledge in this advancing technology.
Please Note: This is an On Demand product, delivery may take up to 11 working days after payment has been received.
Table of Contents
Section 1: Introduction to Artificial Intelligence
1. Data Processing
2. Regression, Classification, and Clustering Algorithms
3. Deep Learning
Section 2: Application of Artificial Intelligence in Disease Diagnosis
4. Application of Artificial Intelligence in Pioneering Heart Disease Detection
5. From Data to Diagnosis: Leveraging Machine Learning for Heart Disease Classification with the Cleveland Heart Disease Dataset
6. AI-based Treatment Solutions
7. Application of AI in Big Data Management
Section 3: AI in Health Monitoring and Wearables Devices
8. Remote Health Monitoring Using Artificial Intelligence
9. Predicting Women’s Fertility with AI
10. A Comparative Study on “Face Mask Detection” Using Machine Learning and Deep Learning Algorithms
11. Enhancing Communication: A Review on AI Wearables for the Deaf and Mute
12. AI based cuffless digital sphygmomanometric measuring system for chronic illness patients
Section 4: Application of AI Medical Image Recognition
13. Identifying Cardiovascular Abnormalities
14. Non-linear Activation Functions of CNN for Classification of MRI Brain tumor Images
15. Artificial Intelligence-Based Management Prospects of Neurological Disorders with Special Reference to Epilepsy
16. Screening for Common Cancers
Authors
Sudip Paul Associate Professor, Department of Biomedical Engineering, School of Technology, North-Eastern Hill University, Shillong, India. Dr. Sudip Paul, Post-Doctoral Fellow and PhD, is currently an Associate Professor & Teacher In-Charge in the Department of Biomedical Engineering, School of Technology, North-Eastern Hill University (NEHU), Shillong, India. He has published over 40 journal papers, over 35 conference papers, and has contributed his knowledge as editorial board member and reviewer for multiple international journals. He has been granted one patent of eight filled and completed more than ten book projects. Dr. Sudip has presented his research accomplishments in countries around the world. He is a member of multiple societies and professional bodies, including APSN, ISN, IBRO, SNCI, SfN, IEEE, IAS. Dr. Sudip has received many awards, including the World Federation of Neurology (WFN) traveling fellowship, Young Investigator Award, IBRO Travel Awardee, and ISN Travel Awardee. Jasjit S. Suri Chairman, AtheroPoint LLC, USA.Dr. Jasjit Suri, PhD, MBA, is a renowned innovator and scientist. He received the Director General's Gold Medal in 1980 and is a Fellow of several prestigious organizations, including the American Institute of Medical and Biological Engineering and the Institute of Electrical and Electronics Engineers. Dr. Suri has been honored with lifetime achievement awards from Marcus, NJ, USA, and Graphics Era University, India. He has published nearly 300 peer-reviewed AI articles, 100 books, and holds 100 innovations/trademarks, achieving an H-index of nearly 100 with about 43,000 citations. Dr. Suri has served as chairman of AtheroPoint, IEEE Denver section, and as an advisory board member to various healthcare industries and universities globally.
