Computational Intelligence in Healthcare Applications

Computational Intelligence in Healthcare Applications

1st Edition - July 14, 2022

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  • Editors: Rajeev Agrawal, M. A. Ansari, R. S. Anand, Sweta Sneha, Rajat Mehrotra
  • Paperback ISBN: 9780323990318
  • eBook ISBN: 9780323993746

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Description

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.

Key Features

  • 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

Readership

Graduate students and researchers on medical informatics. Healthcare workers and stakeholders involved in health technology

Table of Contents

  • 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
  • Abstract
  • Introduction
  • Benefits of AI clinical decision support system
  • Potential challenges associated with AI system
  • U-Net architecture for the decision support system and clinical diagnosis
  • Case study on segmentation of pneumothorax from chest X-ray
  • Comparison of fully connected network (FCN) and U-Net for pneumothorax segmentation
  • Performance metric
  • Conclusion
  • References
  • Chapter 2: Opportunities and challenges for smart healthcare system in fog computing
  • Abstract
  • Introduction
  • Preliminaries
  • Related work
  • Case study
  • Discussion and open issues
  • Conclusion
  • References
  • Chapter 3: Contemporary overview of bacterial vaginosis in conventional and complementary and alternative medicine
  • Abstract
  • Introduction
  • Epidemiology
  • Pathophysiology
  • Clinical features
  • Diagnosis
  • Complications
  • Management
  • Conclusion
  • References
  • Chapter 4: Computer-aided knee joint MR image segmentation—An overview
  • Abstract
  • Introduction
  • Knee MR image segmentation
  • Configurations with mathematical forms
  • Classification processes
  • Conclusion and future trends
  • References
  • Chapter 5: Computational approach to assess mucormycosis: A systematic review
  • Abstract
  • Introduction
  • Computational approach in mucormycosis
  • Mucormycosis association with COVID-19
  • Diseases act as risk factors of mucormycosis
  • Statistical analysis for identification of high-risk factors
  • Conclusion
  • References
  • Chapter 6: A review of diabetes management tools and applications
  • Abstract
  • Introduction
  • Background
  • Review of tools
  • Discussion
  • Conclusion
  • References
  • Further reading
  • Chapter 7: Recent advancements of pelvic inflammatory disease: A review on evidence-based medicine
  • Abstract
  • Acknowledgments
  • Introduction
  • Historical perspectives
  • Epidemiology
  • Aetiopathogenesis
  • Clinical characteristics
  • Diagnosis
  • Investigations
  • Differential diagnosis
  • Complications
  • Management
  • Complementary and alternative medicine (CAM)
  • Conclusion
  • References
  • Chapter 8: A review of amenorrhea toward Unani to modern system with emerging technology: Current advancements, research gap, and future direction
  • Abstract
  • Acknowledgments
  • Introduction
  • Etiology of the amenorrhea
  • Unani concept of amenorrhoea (Ihtibas Al-Tamth)
  • Diagnosis
  • Treatment
  • Modern technology
  • Research gaps and future directions
  • Conclusion
  • References
  • Chapter 9: Wearable EEG technology for the brain-computer interface
  • Abstract
  • Introduction
  • Wireless EEG data acquisition
  • Brief overview of available wireless EEG headsets and headbands
  • Electrode-skin impedance
  • Various electrode technologies used in wearable EEG devices
  • Summary
  • References
  • Chapter 10: Automatic epileptic seizure detection based on the discrete wavelet transform approach using an artificial neural network classifier on the scalp electroencephalogram signal
  • Abstract
  • Acknowledgments
  • Introduction
  • Materials and methods
  • Results
  • Discussion
  • Conclusion
  • References
  • Chapter 11: Event identification by fusing EEG and EMG signals
  • Abstract
  • Introduction
  • Experimental procedure and data analysis
  • Data processing
  • Statistical analysis
  • Results
  • Conclusion
  • References
  • Chapter 12: Hand gesture recognition for the prediction of Alzheimer's disease
  • Abstract
  • Alzheimer’s disease and gestures
  • Literature survey
  • Proposed model
  • Result and discussion
  • Conclusion and future work
  • References
  • Chapter 13: A frequency analysis-based apnea detection algorithm using photoplethysmography
  • Abstract
  • Introduction
  • Method of obtaining a PPG
  • Steps involved in apnea detection through PPG
  • Results and discussion
  • Conclusion
  • References
  • Chapter 14: Noninvasive health monitoring using bioelectrical impedance analysis
  • Abstract
  • Introduction
  • Principles of bioelectrical impedance analysis (BIA)
  • Conclusion
  • References
  • Chapter 15: Detection of cancer from histopathology medical image data using ML with CNN ResNet-50 architecture
  • Abstract
  • Introduction
  • Related work
  • Cancer detection process
  • Application of machine learning in cancer detection
  • Input dataset
  • Proposed methodology
  • Experimental results and discussion
  • Conclusion
  • References
  • Chapter 16: Performance analysis of augmented data for enhanced brain tumor image classification using transfer learning
  • Abstract
  • Introduction
  • Related work
  • Pipeline and implementation
  • Dataset description
  • Results and accuracy
  • Conclusion and future scope
  • References
  • Chapter 17: Brain tumor detection through MRI using image thresholding, k-means, and watershed segmentation
  • Abstract
  • Introduction
  • Literature review
  • Methodology
  • Filtration techniques
  • Segmentation techniques
  • Feature extraction
  • Implementation
  • Results and discussion
  • Conclusion
  • Limitations and future scope
  • References
  • Chapter 18: An intelligent diagnostic technique using deep convolutional neural network
  • Abstract
  • Introduction
  • Related works
  • Proposed approach
  • Dataset used
  • Experimental results
  • Discussion
  • Conclusion
  • References
  • Chapter 19: Design of a biosensor for the detection of glucose concentration in urine using 2D photonic crystals
  • Abstract
  • Introduction
  • Design of a biosensor
  • Simulation and result
  • Conclusion
  • References
  • Chapter 20: Classification of pneumonic infections through chest radiography using textural features analysis and the pattern recognition system
  • Abstract
  • Introduction
  • State of the art
  • Proposed methodology
  • Results of network evaluation
  • Conclusion
  • References
  • Chapter 21: Convolutional bi-directional long-short-term-memory based model to forecast COVID-19 in Algeria
  • Abstract
  • Acknowledgment
  • Funding information
  • Conflicts of interest
  • Ethical approval
  • Informed consent
  • Introduction
  • Related works
  • Data sources
  • Methods
  • Experiment
  • Results
  • Conclusion
  • References
  • Index

Product details

  • No. of pages: 376
  • Language: English
  • Copyright: © Academic Press 2022
  • Published: July 14, 2022
  • Imprint: Academic Press
  • Paperback ISBN: 9780323990318
  • eBook ISBN: 9780323993746

About the Editors

Rajeev Agrawal

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

Affiliations and Expertise

Director, GL Bajaj Institute of Technology and Management, India

M. A. Ansari

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.

Affiliations and Expertise

Professor, School of Engineering, Gautam Buddha University, India

R. S. Anand

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

Affiliations and Expertise

Department of Electrical Engineering, IIT Roorkee, India

Sweta Sneha

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

Affiliations and Expertise

Michael J. Coles College of Business, Kennesaw State University, USA

Rajat Mehrotra

Rajat Mehrotra works in the Department of Electronical and Electronics Engineering at GL Bajaj Institute of Technology and Management, India.

Affiliations and Expertise

Department of Electronical and Electronics Engineering, GL Bajaj Institute of Technology and Management, India

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