Computational Intelligence in Healthcare Applications

Rajeev Agrawal, M. A. Ansari, R. S. Anand, Sweta Sneha, Rajat Mehrotra

• Publisher: Academic Press
• Year: 2022
• Print ISBN: 9780323990318
• eBook ISBN: 9780323993746
• Topic: Biological Sciences
• Subtopic: Bioinformatics
• Index: Biological Sciences

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

Table of contents

• Title of Book
• Cover image
• Title page
• Table of Contents
• Copyright
• Contributors
• About the editors
• Preface
• Acknowledgments
• Chapter 1 Clinical decision support systems: Benefits, potential challenges, and applications in pneumothorax segmentation
• Chapter 2 Opportunities and challenges for smart healthcare system in fog computing
• Chapter 3 Contemporary overview of bacterial vaginosis in conventional and complementary and alternative medicine
• Chapter 4 Computer-aided knee joint MR image segmentation—An overview
• Chapter 5 Computational approach to assess mucormycosis: A systematic review
• Chapter 6 A review of diabetes management tools and applications
• Chapter 7 Recent advancements of pelvic inflammatory disease: A review on evidence-based medicine
• Chapter 8 A review of amenorrhea toward Unani to modern system with emerging technology: Current advancements, research gap, and future direction
• Chapter 9 Wearable EEG technology for the brain-computer interface
• Chapter 10 Automatic epileptic seizure detection based on the discrete wavelet transform approach using an artificial neural network classifier on the scalp electroencephalogram signal
• Chapter 11 Event identification by fusing EEG and EMG signals
• Chapter 12 Hand gesture recognition for the prediction of Alzheimer's disease
• Chapter 13 A frequency analysis-based apnea detection algorithm using photoplethysmography
• Chapter 14 Noninvasive health monitoring using bioelectrical impedance analysis
• Chapter 15 Detection of cancer from histopathology medical image data using ML with CNN ResNet-50 architecture
• Chapter 16 Performance analysis of augmented data for enhanced brain tumor image classification using transfer learning
• Chapter 17 Brain tumor detection through MRI using image thresholding, k-means, and watershed segmentation
• Chapter 18 An intelligent diagnostic technique using deep convolutional neural network
• Chapter 19 Design of a biosensor for the detection of glucose concentration in urine using 2D photonic crystals
• Chapter 20 Classification of pneumonic infections through chest radiography using textural features analysis and the pattern recognition system
• Chapter 21 Convolutional bi-directional long-short-term-memory based model to forecast COVID-19 in Algeria
• Index