Computational Intelligence in Medical Decision Making and Diagnosis

Techniques and Applications

Sitendra Tamrakar, Shruti Bhargava Choubey, Abhishek Choubey

• Publisher: CRC Press
• Year: 2023
• ISBN:
  9781000853926
• Edition: 1
• Topic: Medicine
• Subtopic: Biotechnology in Medicine

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 medical diagnosis, like uncertainties in the medical domain, problems in the medical data, especially dealing with time-stamped data, and knowledge acquisition.

Features:

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• Introduces recent applications of new computational intelligence technologies focusing on medical diagnosis issues.

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• Reviews multidisciplinary research in health care, like data mining, medical imaging, pattern recognition, and so forth.

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• Explores intelligent systems and applications of learning in health-care challenges, along with the representation and reasoning of clinical uncertainty.

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• Addresses problems resulting from automated data collection in modern hospitals, with possible solutions to support medical decision-making systems.

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• Discusses current and emerging intelligent systems with respect to evolutionary computation and its applications in the 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

• Cover
• Half Title
• Series
• Title
• Copyright
• Dedication
• Table of Contents
• About the Editors
• List of Contributors
• Preface
• Chapter 1 Prediction of Diseases Using Machine Learning Techniques
• Chapter 2 A Novel Virtual Medicinal Care Model for Remote Treatments
• Chapter 3 Artificial Intelligence in Future Telepsychiatry and Psychotherapy for E-Mental Health Revolution
• Chapter 4 Optimized Convolutional Neural Network for Classification of Tumors from MR Brain Images
• Chapter 5 Predictive Modeling of Epidemic Diseases Based on Vector-Borne Diseases Using Artificial Intelligence Techniques
• Chapter 6 Hybrid Neural Network-Based Fuzzy Inference System Combined with Machine Learning to Detect and Segment Kidnev Tumor
• Chapter 7 Classification of Breast Tumor from Histopathological Images with Transfer Learning
• Chapter 8 Performance of IoT-Enabled Devices in Remote Health Monitoring Applications
• Chapter 9 Applying Machine Learning Logistic Regression Model for Predicting Diabetes in Women
• Chapter 10 Compressive Sensing-Based Medical Imaging Techniques to Detect the Type of Pneumonia in Lungs
• Chapter 11 Electroencephalogram (EEG) Signal Denoising Using Optimized Wavelet Transform (WT): A Study
• Chapter 12 Predicting Diabetes in Women by Applying the Support Vector Machine (SVM) Model
• Chapter 13 Data Mining Approaches on EHR System: A Survey
• Chapter 14 Chest Tumor Identification in Mammograms by Selected Features Employing SVM
• Chapter 15 A Novel Optimum Clustering Method Using Variant of NOA
• Chapter 16 Role of Artificial Intelligence and Neural Network in the Health-Care Sector: An Important Guide for Health Prominence
• Index