Computational Intelligence in Healthcare Applications - Softcover

Softcover

ISBN 10: 0323990312 ISBN 13: 9780323990318

Publisher: Academic Press, 2022

Synopsis

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.

• Presents advanced procedures to address and enhance available diagnostic methods
• Focuses on identifying challenges and solutions through an integrated approach that shapes a path for new research dimensions
• Discusses the implementation of deep learning techniques for the detection and classification of diseases

About this title

About the Authors

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

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 works in the Department of Electrical Engineering at IIT Roorkee, India.

Sweta Sneha works in the Michael J. Coles College of Business at Kennesaw State University, USA.

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.

From the Back Cover

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. It serves as a reference for pervasive healthcare domain which takes into consideration future and beyond the 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.It is a valuable resource for graduate students and researchers in medical informatics, and members of biomedical field and healthcare industry who are interested in learning more about novel technologies and their application in the field.

Edition details

• Publisher: Academic Press
• Publication date: 2022
• Language: English
• ISBN 10: 0323990312
• ISBN 13: 9780323990318
• Binding: Paperback
• Number of pages: 374
• Editor: Agrawal, Ansari, Anand, Sneha, Mehrotra