Computational Intelligence in Healthcare

Computational intelligence (CI) refers to the ability of computers to accomplish tasks that are normally completed by intelligent beings such as humans and animals. Artificial intelligent systems offer great improvement in healthcare systems by providing more intelligent and convenient solutions and services assisted by machine learning, wireless communications, data analytics, cognitive computing, and mobile computing. Modern health treatments are faced with the challenge of acquiring, analysing, and applying the large amount of knowledge necessary to solve complex problems. AI techniques are being effectively used in the field of healthcare systems by extracting the useful information from the vast amounts of data by applying human expertise and CI methods, such as fuzzy models, artificial neural networks, evolutionary algorithms, and probabilistic methods which have recently emerged as promising tools for the development and application of intelligent systems in healthcare practice. This book starts with the fundamentals of computer intelligence and the techniques and procedures associated with them. Contained in the book are state-of-the-art CI methods and other allied techniques used in healthcare systems as well as advances in different CI methods that confront the problem of effective data analysis and storage faced by healthcare institutions. The objective of this book is to provide the latest research related to the healthcare sector to researchers and engineers with a platform encompassing state-of-the-art innovations, research and design, and the implementation of methodologies.

Dr. Meenu Gupta is an Associate Professor at the UIE-CSE Department, Chandigarh University, India. She has completed her PhD degree in Computer Science and Engineering with emphasis on Traffic Accident Severity Problems from Ansal University, Gurgaon, India, year 2020. She has more than 13 years of teaching experience. Her areas of research cover the fields of Machine Learning, Intelligent Systems, Data mining, with a specific interest in Artificial Intelligence, Smart Cities, etc. She has edited two books on Healthcare and Cancer diseases and authored four engineering books. She works as a reviewer for several journals including Soft Computing, Big Data, Scientific Report, and etc. She is a life member of ISTE and IAENG. She has authored or co-authored more than 20 book chapters and over 60 papers in refereed international journals and conferences. She has filled 3 Indian patents and awarded with best faculty and researcher of the department in year 2021. Dr. Shakeel Ahmed is Associate Professor at the College of Computer Sciences and Information Technology, King Faisal University, Saudi Arabia. His areas of interest include Software Verification and Validation, Mobile AdHoc Networks, Software Engineering, and Cloud Computing. He is the head of the cloud computing research group at the College of Computer Sciences and Information technology, KFU. He has authored several research papers in indexed and impact factor research journals and IEEE international conferences. He is a PC member for several international conferences and an active reviewer for quartile journals. He holds a Ph.D. degree in Computer Science from Indore University, India. Dr. Rakesh Kumar is a Professor in the Department of Computer Science Engineering at Chandigarh University, Punjab, India. He has done his Ph.D. in Computer Science and Engineering from Punjab Technical University, Jalandhar, year 2017. He has more than 17 years of teaching experience. His research interests are IoT, Machine Learning and Natural Language Processing. He has published many authored books with reputed publisher. He works as a reviewer for several journals including Big Data, CMC, Scientific Report and TSP. He has authored or co-authored more than 50 publications various National, International Conferences and International Journals. He is also working as a PI in AIMS funding project with collaboration of Chandigarh University, Punjab. Chadi Altrjman is working as an associate scientist and researcher in Near East University, Cyprus and received his Bachelor of Engineering from the University of Waterloo, Ontario, Canada. And now, he is involved in several smart projects via which he is expanding his practical skills. His research interests include AI and machine learning, Wireless Sensor Networks, Chemical Sensors, Sustainable & Renewable Energy Integration, Distributed Power Generation, and Smart Grid Applications.

1. Introduction to Computational Intelligence in Healthcare: Applications, Challenges, and Management, 2. Role of IoT and Machine Learning for E-Healthcare Management, 3. Telemedical and Remote Healthcare Monitoring Using IoT and Machine Learning, 4. Efficient Ways for Healthcare Data Management Using Data Science and Machine Learning, 5. A Novel Scheme to Manage the E-Healthcare System Using Cloud Computing and the Internet of Things, 6. Automating Remote Point-of-Care ECG Diagnostics via Decentralized Report Routing Algorithm, 7. Evaluation of Deep Image Embedders for Healthcare Informatics Improvement Using Visualized Performance Metrics, 8. A Comparative Analysis for Analysing the Performance of Convolutional Neural Network versus Other Machine Learning Techniques to Assess Cardiovascular Disease, 9. A Study of Machine Learning Initiatives in the Global Healthcare Sector Using Different Case Studies, 10. Autism Spectrum Disorder Diagnostic System Using Adaptive Neuro Fuzzy Inference System, 11. Detection of Diabetic Foot Ulcer (DFU) With AlexNet and ResNet-101, 12. A Case Study-Based Analysis on Remote Medical Monitoring with AWS Cloud and Internet of Things (IoT)

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