Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data
- 1st Edition - January 22, 2022
- Latest edition
- Editors: Akash Kumar Bhoi, Victor Hugo Costa de Albuquerque, Parvathaneni Naga Srinivasu, Goncalo Marques
- Language: English
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
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Description
Description
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.
Key features
Key features
- 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
Readership
Readership
Industries, Professionals, Academicians, Researchers and post graduate students in Data processing, Predictive analysis, Machine Learning Algorithms, and Computational Intelligence in data engineering systems. Graduate students in Computer Science Engineering, Data Science Engineering and Machine Learning based engineering courses
Table of contents
Table of contents
Section 1: Cognitive Technology for processing of Healthcare data
1. Cognitive technology in personalized Medicine/healthcare solutions
2. Cognitive technology for blend of personalized healthcare information with scientific data for better clinical risk analysis and healthcare innovation
3. Healthcare data encryption, data processing for the data acquired from smart sensors and approaches
Section 2: Artificial Intelligence Approaches for Healthcare Industry
4. Artificial Neural Networks based approaches for computer-aided disease diagnosis and treatment
5. AI and Deep Learning for processing the huge amount of patient centric data that assists in clinical decisions
6. Pattern Recognition and Computer vision approaches for handling healthcare data
7. 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 Analysis
8. Optimization inspired by biological evolution for high dimensional data for forecasting of illness in advance like Cancer, Heart disease, Brain tumors
9. Swarm Intelligence and Evolutionary Algorithms in processing the Healthcare Data
10. 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 industry
11. Natural computing and Unsupervised Learning Methods in healthcare data-centric operations
12. Soft Computing and Machine Learning Techniques for healthcare data analytics
13. Probabilistic approaches for minimizing the healthcare diagnosis cost through data-centric operations
14. Computational Intelligence in Human-machine interface (HMI) e.g. ECG, EEG, EMG, PCG and predictive data analysis
Product details
Product details
- Edition: 1
- Latest edition
- Published: January 24, 2022
- Language: English
About the editors
About the editors
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Akash Kumar Bhoi
Dr. Akash Kumar Bhoi accomplished academic and researcher with over a decade of experience in Computer Science and Engineering, Artificial Intelligence, Machine Learning, Data Science, and Biomedical Computing. Recognized globally for research excellence, ranked in the Top 0.5% of Scholars worldwide (ScholarGPS, 2024 & 2025) and listed among the World’s Top 2% Scientists (Stanford University & Elsevier, 2022, 2023 & 2025). Prolific contributor with 200+ Scopus-indexed publications, multiple edited books with Springer/Elsevier, and an h-index of 39 (Google Scholar). Dr. Bhoi is currently associated with Graphic Era Deemed to be University, Dehradun. More than a decade of academic & research experience in India, Italy, Australia, and South Korea. Expertise spans computational intelligence, data analytics, healthcare informatics, biomedical signal and image processing, cloud/edge computing, and IoT applications.
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Victor Hugo Costa de Albuquerque
PS
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.
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