Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data

by Akash Kumar Bhoi PhD. (Editor), PhD de Albuquerque MSc (Editor), Parvathaneni Naga Srinivasu (Editor), Goncalo Marques (Editor)

Overview

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. - Focuses on data-centric operations in the Healthcare industry - Provides the latest trends in healthcare data analytics and practical implementation outcomes of the proposed models - Addresses real-time challenges and case studies in the Healthcare industry

Product Details

ISBN-13:	9780323903486
Publisher:	Elsevier Science & Technology Books
Publication date:	01/22/2022
Series:	Intelligent Data-Centric Systems
Sold by:	Barnes & Noble
Format:	eBook
Pages:	294
File size:	49 MB
Note:	This product may take a few minutes to download.

About the Author

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. In addition to his academic responsibilities, Dr. Bhoi extended his expertise during a research tenure as a Research Associate at the Wireless Networks (WN) Research Laboratory, Institute of Information Science and Technologies, National Research Council (ISTI-CRN) in Pisa, Italy, from January 20, 2021, to January 19, 2022. Dr. Bhoi further 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 Indian and 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. Dr. Bhoi has played a pivotal role in the organization of international conferences and workshops, offering his expertise as a key contributor. Currently, he is involved in editing several books in collaboration with international publishers
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.
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.
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.

Table of Contents

Section 1: Cognitive Technology for processing of Healthcare data 1. Cognitive technology in personalized Medicine/healthcare solutions2. Cognitive technology for blend of personalized healthcare information with scientific data for better clinical risk analysis and healthcare innovation3. Healthcare data encryption, data processing for the data acquired from smart sensors and approaches Section 2: Artificial Intelligence Approaches for Healthcare Industry4. Artificial Neural Networks based approaches for computer-aided disease diagnosis and treatment5. AI and Deep Learning for processing the huge amount of patient centric data that assists in clinical decisions6. Pattern Recognition and Computer vision approaches for handling healthcare data7. Applications of Recurrent Neural Networks, Generative Neural Networks, Ensemble methods, Weakly Trained Approaches towards Data associated with healthcare solutions Section 3: Evolutionary Algorithms for Healthcare Data Analysis8. Optimization inspired by biological evolution for high dimensional data for forecasting of illness in advance like Cancer, Heart disease, Brain tumors9. Swarm Intelligence and Evolutionary Algorithms in processing the Healthcare Data10. Recent advancements in evolutionary algorithms for handling the information related to healthcare industry Section4: Computational Intelligence and soft computing models in processing the data related to healthcare industry11. Natural computing and Unsupervised Learning Methods in healthcare data-centric operations12. Soft Computing and Machine Learning Techniques for healthcare data analytics13. Probabilistic approaches for minimizing the healthcare diagnosis cost through data-centric operations14. Computational Intelligence in Human-machine interface (HMI) e.g. ECG, EEG, EMG, PCG and predictive data analysis

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From the Publisher

Presents the latest trends in data processing for risk analysis and innovation in the healthcare industry