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Computational Intelligence in Healthcare Applications

  • Book

  • July 2022
  • Elsevier Science and Technology
  • ID: 5527478

Computational Intelligence in Healthcare Applications discusses a variety of techniques designed to represent, enhance and empower inter-domain research based on computational intelligence in healthcare. The book serves as a reference for the pervasive healthcare domain which takes into consideration new convergent computing and other applications. The book discusses topics such as mathematical modeling in medical imaging, predictive modeling based on artificial intelligence and deep learning, smart healthcare and wearable devices, and evidence-based predictive modeling. In addition, it discusses computer-aided diagnostic for clinical inferences and pervasive and ubiquitous techniques in healthcare.

This book is a valuable resource for graduate students and researchers in medical informatics, however, it is also ideal for members of the biomedical field and healthcare industry who are interested in learning more about novel technologies and their applications in the field.

Please Note: This is an On Demand product, delivery may take up to 11 working days after payment has been received.

Table of Contents

1. Mathematical Modeling and its significance in the field of Medical Imaging2. Modeling of Healthcare services and its influence on human health3. Health care applications design and development4. Predictive modeling based on Artificial Intelligence and Deep Learning5. Smart health care /wearable devices and their applications6. Detection and Classification of different medical disorders using Artificial Intelligence and Deep Learning techniques7. Prediction of neurological disorders using MRI and other imaging techniques8. Evidence-based predictive modeling using soft computing9. Decision support system for clinical applications using AI and other learning techniques10. Knowledge-based management system for health care services and usage11. Computer-aided diagnostic for clinical inferences12. Pervasive and ubiquitous techniques in healthcare

Authors

Rajeev Agrawal Director, GL Bajaj Institute of Technology and Management, India. Dr. Rajeev Agrawal holds PhD degree on Computer Science from Jawaharlal Nehru University. He has more than 27 years of experience in teaching and research. He was Head of Computer Science Department at Kumaon Engineering College and currently is Director at GL Bajaj Institute of Technology and Management. He holds four patents, received several grants for research projects and is editorial board member of Health Informatics Journal (Sage). Dr. Agrawal main research interests are m-health, medical imaging and wireless networks M. A. Ansari Professor, School of Engineering, Gautam Buddha University, India. Dr. M.A. Ansari holds PhD degree on Signal and Imaging Processing from Indian Institute of Technology Roorkee. He has 18 years of experience in teaching and research. Currently he is Professor at School of Engineering, Gautam Buddha University, where he supervised 4 PhD and 63 MTech students to date. He authored several book chapters and published almost 30 peer-reviewed articles in international journals. Dr. Ansari main research interests are medical image coding, biomedical instrumentation and control, and digital signal and image processing. R. S. Anand Department of Electrical Engineering, IIT Roorkee, India. R.S. Anand works in the Department of Electrical Engineering at IIT Roorkee, India. Sweta Sneha Michael J. Coles College of Business, Kennesaw State University, USA. Sweta Sneha works in the Michael J. Coles College of Business at Kennesaw State University, USA. Rajat Mehrotra Bajaj Institute of Technology ,GL Bajaj Institute of Technology & Management, Greater Noida, India. Rajat Mehrotra is an Assistant Professor in the Electrical & Electronics Engineering Department at GL Bajaj Institute of Technology & Management, Greater Noida, India. He received his BTech in Electrical and Electronics Engineering from the Dr. A.P.J. Abdul Kalam Technical University, Lucknow (Formerly UPTU), in 2008 and his MTech in Telecommunication Engineering from the same university, in 2014 and his PhD. in the field of Medical Image Processing. His research interests include digital image processing, biomedical imaging, and deep learning. Currently, he is involved in research with the School of Engineering at Gautam Buddha University, Greater Noida. He has published his research in various journals of international repute. He has more than 14 years of experience in teaching and research. He has also published multiple patents in his area of research.