Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data

1st Edition - January 22, 2022
Editors: Akash Kumar Bhoi, Victor Hugo Costa de Albuquerque, Parvathaneni Naga Srinivasu, Goncalo Marques
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 8 5 7 5 1 - 2
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 0 3 4 8 - 6

Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data discusses the insight of data processing applications in various domains through soft computing… Read more

Purchase options

LIMITED OFFER

Save 50% on book bundles

Immediately download your ebook while waiting for your print delivery. No promo code is needed.

Institutional subscription on ScienceDirect

Request a sales quote

Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data discusses the insight of data processing applications in various domains through soft computing techniques and enormous advancements in the field.

The book focuses on the cross-disciplinary mechanisms and ground-breaking research ideas on novel techniques and data processing approaches in handling structured and unstructured healthcare data. It also gives insight into various information-processing models and many memories associated with it while processing the information for forecasting future trends and decision making.

This book is an excellent resource for researchers and professionals who work in the Healthcare Industry, Data Science, and Machine learning.

Cover image
Title page
Table of Contents
Copyright
Contributors
Preface
Chapter 1. Artificial intelligence and machine learning for the healthcare sector: performing predictions and metrics evaluation of ML classifiers on a diabetic diseases data set
1. Introduction
2. Smart healthcare system
3. Machine learning example of data analytics in health care
4. Experimental results
5. Conclusion
Abbreviations
Chapter 2. Cognitive technology for a personalized seizure predictive and healthcare analytic device
1. Introduction
2. Epilepsy and seizures
3. Cognitive technology
4. Internet of Things
5. Cognitive IoT and neural networks
6. Natural language processing
7. Problem statement
8. Methodology
9. Proposed approach
10. Simulations and discussions
11. Conclusions
Chapter 3. Cognitive Internet of Things (IoT) and computational intelligence for mental well-being
1. Introduction
2. Cognitive IoT and computational intelligence in health care
3. Computer vision for early diagnosis of mental disorders using MRI
4. Feature selection techniques and optimization techniques used
5. Natural language processing-based diagnostic system
6. Harnessing the power of NLP for the analysis of social media content for depression detection
7. Computational intelligence and cognitive IoT in suicide prevention
8. Wearables and IoT devices for mental well-being
9. Future scope of computational intelligence in mental well-being
10. Conclusion
Chapter 4. Artificial neural network-based approaches for computer-aided disease diagnosis and treatment
1. Introduction
2. Artificial neural networks applied to computer-aided diagnosis and treatment
3. Application of ANN in the diagnosis and treatment of cardiovascular diseases
4. Case study: ANN and medical imaging—brain tumor detection
5. Final considerations
Chapter 5. AI and deep learning for processing the huge amount of patient-centric data that assist in clinical decisions
1. Introduction
2. Challenges and trends
3. Case study 1: multiple Internet of Things (IoT) monitoring systems and deep learning classification systems to support ambulatory maternal–fetal clinical decisions
4. Case study 2: artificial intelligence epidemiology prediction system during the COVID-19 pandemic to assist in clinical decisions
5. Final considerations
Chapter 6. Universal intraensemble method using nonlinear AI techniques for regression modeling of small medical data sets
1. Introduction and problem statement
2. Related concepts
3. Universal intraensemble method for handling small medical data
4. Practical implementation
5. Comparison and discussion
6. Conclusion and future work
Appendix A
Chapter 7. Comparisons among different stochastic selections of activation layers for convolutional neural networks for health care
1. Introduction
2. Literature review
3. Activation functions
4. Materials and methods
5. Results
6. Conclusions
Chapter 8. Natural computing and unsupervised learning methods in smart healthcare data-centric operations
1. Introduction
2. Natural computing in the healthcare industry
3. Unsupervised learning techniques in healthcare systems
4. The data-centric operations in healthcare systems
5. Case study for application of the particle swarm optimization model for the diagnosis of heart disease
6. Results and discussion
7. Conclusion
Chapter 9. Optimized adaptive tree seed Kalman filter for a diabetes recommendation system—bilevel performance improvement strategy for healthcare applications
1. Introduction
2. Literature review
3. The proposed AKF-TSA-based insulin recommendation system
4. Results and discussion
5. Conclusion
Chapter 10. Unsupervised deep learning-based disease diagnosis using medical images
1. Introduction
2. Related works
3. Methodology
4. Experiments
5. Evaluation metrics
6. Experimental results and discussions
7. Conclusion
8. Future work
Chapter 11. Probabilistic approaches for minimizing the healthcare diagnosis cost through data-centric operations
1. Introduction
2. Bayesian neural networks
3. Markov chain Monte Carlo (MCMC)
4. Breast cancer prediction using a Bayesian neural network
5. Conclusion
Chapter 12. Effects of EEG-sleep irregularities and its behavioral aspects: review and analysis
1. Introduction
2. Medical background
3. Visual scoring procedure
4. AI and sleep staging
5. Sleep patterns and clinical age
6. Case study of an automated sleep staging system
7. Chapter outcome and conclusion
Index

Akash Kumar Bhoi

Dr. Akash Kumar Bhoi, holds degrees in B.Tech, M.Tech, and Ph.D., and has been contributing to the field of computer science and engineering. He assumed the role of Assistant Professor (Research) at the Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology (SMIT), India, in 2012. Dr. Bhoi serves as the University Ph.D. Course Coordinator for "Research & Publication Ethics (RPE)." He is an active member of professional organizations such as IEEE, ISEIS, and IAENG, and holds associate membership with IEI and UACEE. He plays a significant role as an editorial board member and reviewer for esteemed international journals and regularly contributes as a reviewer. His research expertise encompasses a wide array of domains, including Biomedical Technologies, the Internet of Things, Computational Intelligence, Antenna technology, and Renewable Energy. Dr. Bhoi has a notable publication record, with multiple papers featured in national and international journals and conferences.

Affiliations and expertise

Assistant Professor, Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Sikkim, India

Victor Hugo Costa de Albuquerque

Victor Hugo C. de Albuquerque [M’17, SM’19] is a collaborator Professor and senior researcher at the Graduate Program on Teleinformatics Engineering at the Federal University of Ceará, Brazil, and at the Graduate Program on Telecommunication Engineering, Federal Institute of Education, Science and Technology of Ceará, Fortaleza/CE, Brazil. He has a Ph.D in Mechanical Engineering from the Federal University of Paraíba (UFPB, 2010), an MSc in Teleinformatics Engineering from the Federal University of Ceará (UFC, 2007), and he graduated in Mechatronics Engineering at the Federal Center of Technological Education of Ceará (CEFETCE, 2006). He is a specialist, mainly, in Image Data Science, IoT, Machine/Deep Learning, Pattern Recognition, Robotic.

Affiliations and expertise

Professor and Senior Researcher, Federal University of Ceara, Fortaleza, Graduate Program on Teleinformatics Engineering,Fortaleza/CE, Brazil

Parvathaneni Naga Srinivasu

Parvathaneni Naga Srinivasu has earned his Ph.D. degree at GITAM (Deemed to be University) and his areas of research include Biomedical Imaging, Image Enhancement, Image Segmentation, Object Recognition, Image Encryption, Optimization Algorithms, Soft computing, and Natural Language Processing. He is working as an Assistant Professor at the Department of Computer Science and Engineering, GIT, GITAM (Deemed to be University), Visakhapatnam. He is a member of CSI, IAENG, IARA and a regular reviewer for Scopus indexed journals like JCS and IJAIP, Inderscience. He is a guest editor for the special issues and books that are published by reputed publishers like Bentham Science, Springer, and Elsevier. He is a passionate researcher and his articles have been published in national and international journals alongside conferences.

Affiliations and expertise

Assistant Professor at the Department of Computer Science and Engineering, GIT, GITAM (Deemed to be University), Visakhapatnam, India

Goncalo Marques

Gonçalo Marques holds a PhD in Computer Science Engineering and is member of the Portuguese Engineering Association (Ordem dos Engenheiros). He is currently working as Assistant Professor lecturing courses on programming, multimedia and database systems. His current research interests include Internet of Things, Enhanced Living Environments, machine learning, e-health, telemedicine, medical and healthcare systems, indoor air quality monitoring and assessment, and wireless sensor networks. He has more than 80 publications in international journals and conferences, is a frequent reviewer of journals and international conferences and is also involved in several edited books projects.

Affiliations and expertise

Polytechnic of Coimbra, ESTGOH, Rua General Santos Costa, 3400-124 Oliveira do Hospital, Portugal