Computational Intelligence in Medical Decision Making and Diagnosis : Techniques and Applications book cover
1st Edition

Computational Intelligence in Medical Decision Making and Diagnosis
Techniques and Applications

  • Available for pre-order on March 10, 2023. Item will ship after March 31, 2023
ISBN 9781032313771
March 31, 2023 Forthcoming by CRC Press
304 Pages 100 B/W Illustrations

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Book Description

Computation intelligence (CI) paradigms including artificial neural networks, fuzzy systems, evolutionary computing techniques, and intelligent agents form the basis of making clinical decisions. This book explains different aspects of the current research on CI technologies applied in the field of medical diagnosis. It discusses critical issues related to the medical diagnosis like uncertainties in the medical domain, problems in the medical data especially dealing with time-stamped data, and knowledge acquisition.


  • Introduces the recent applications of new computational intelligent technologies focusing on medical diagnosis issues.
  • Reviews multidisciplinary research in healthcare like data mining, medical imaging, pattern recognition and so forth.
  • Explores intelligent systems and application of learning in healthcare challenges along with the representation and reasoning of clinical uncertainty.
  • Addresses the problems resulting from automated data collection in modern hospitals with possible solutions to support medical decision-making system.
  • Discusses current and emerging intelligent system with respect to evolutionary computation and its applications in medical domain.

This book is aimed at researchers, professionals and graduate students in computational intelligence, signal processing, imaging, artificial intelligence, and data analytics

Table of Contents

1. Prediction of Diseases using Machine Learning Techniques. 2. A novel virtual medicinal care model for remote treatments. 3. Artificial Intelligence in Future Telepsychiatry and Psychotherapy for E-Mental Health Revolution. 4 . Optimized Convolutional Neural Network for Classification of Tumors from MR Brain Images. 5. Predictive Modeling of Epidemic Diseases based on Vector-borne diseases using Artificial Intelligence Techniques. 6. Hybrid Neural Network Based Fuzzy Inference System Combined with Machine Learning to Detect and Segment Kidney Tumor. 7. Classification of breast tumor from histopathological images with transfer learning. 8. Performance of IoT Enabled Devices in Remote Health Monitoring Applications. 9. Applying Machine Learning Logistic Regression Model for Predicting the Diabetes in women. 10. Compressive Sensing Based Medical Imaging Techniques to detect the type of Pneumonia in Lungs. 11. Electroencephalogram (EEG) Signal Denoising using Optimized Wavelet Transform (WT): A Study. 12. Predicting the Diabetes in women by Appling Support Vector Machine (SVM) model using Python programming. 13. Data Mining Approaches on EHR System: A Survey. 14. Chest Tumor Identification in Mammograms by Selected Features Employing SVM. 15. A Novel Optimum Clustering Method using Variant of NOA. 16. Role of Artificial Intelligence and Neural Network in healthcare sector: An important guide for health prominent.

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Dr. Sitendra Tamrakar is working as an associate professor and research coordinator in the department of Computer Science & Engineering at Nalla Malla Reddy Engineering College, Hyderabad, Telangana, India. He has more than 17 years of experience in the field of teaching and research. He has guided 05 Ph.D. & 19 M.Tech dissertations. He has authored a total of 92 publications which includes books, research papers & book chapters, which have been published in nationally and internationally. He has 05 patents published and granted with IP Australia and IP India. He had delivered 15 Invited Talks in various national, international conferences and seminars. He has been appointed as reviewers in various journals and conferences. He has attended 35 FDP/workshops and organized 07conferences, FDPs and Workshops. His research interests are focused on the area of artificial intelligence; cloud computing, and computer networks. He is an active member of the Computer Society of India (CSI), Hyderabad Chapter and ACM CSTA.

Dr. Shruti Bhargava Choubey has received her B.E. with honors (2007) from RGPV Bhopal and M. Tech. degree in Digital Communication Engineering (2010) from RGPV Bhopal subsequently she carried out her research form Dr. K. N. Modi University Banasthali Rajasthan, and awarded Ph.D. in 2015. Presently she is working as Associate Professor & Dean Innovation & Research in the Department of Electronics and Communication at Sreenidhi Institute of Science and Technology, Hyderabad she has published more than 100 papers (5 SCI, 18 Scopus) of national and International repute. She has been a Member of many selection committees for recruitment of staff and faculty. Her research areas include signal processing, Image processing and Biomedical Engineering. She has produced 17 M.Tech degrees and guided more than 70 B.Tech Project. She is senior member of IEEE, member of IETE, New Delhi and International Association of Engineers (IAENG). She worked in different positions like Dean academic & HOD with numerous capacities. She was awarded MP Young scientist fellowship 2015 & Received MP council fellowship in 2014 for her contribution to Research.

Dr. Abhishek Choubey has received his Ph.D. degree in the field of VLSI for digital signal processing from Jayppe University and technology Guna MP, in 2017. He is currently associated with Sreenidhi institute of science and technology, Hyderabad, as an Associate Professor. He has published nearly 70 technical articles. His research interest includes reconfigurable architectures, approximate-computation, algorithm design, and implementation of high-performance VLSI systems for signal processing applications. He was a recipient of the Sydney R. Parker and M. N. S. Swamy Best Paper Award for Circuits, Systems, and Signal Processing in 2018.