Artificial Intelligence Applications for Health Care

This book takes an interdisciplinary approach covering health care, cognitive computing, and artificial intelligence. Data sets related to biomedical signals (ECG, EEG, EMG) and images (X-rays, MRI, CT) are explored, analyzed, and processed. Applications of computational intelligence techniques like swarm optimization, expert system, decision support system, clustering and classification techniques in medial datasets are explained. Remote access of health care services through Internet of Things (IoT) applications are also covered. Key Features:Covers computational Intelligence techniques like fuzzy sets, artificial neural networks, deep neural networks, and genetic algorithm for Healthcare systems Provides easy understanding concepts like signal and image filtering techniques Includes discussion over filtering and classification problems Details studies with medical signal (ECG, EEG, EMG) and image (X-rays, FMRI, CT) datasets Describes evolution parameters such as signal-to-noise ratio, mean square error, accuracy, precision, and recall This book is aimed at researchers and graduate students in medical signal and image processing, machine and deep learning, and healthcare technologies.