Cognitive and Meta Learning Strategies in Biomedical Research and Healthcare
- 1st Edition - March 1, 2026
- Editors: Subhendu Kumar Pani, Chinmay Chakraborty, Sayonara Barbosa
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 4 0 3 7 9 - 8
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 4 0 3 8 0 - 4
Cognitive and Meta Learning Strategies in Biomedical Research Healthcare examines the dynamic intersection of cognitive science and meta-learning within the realm of biomed… Read more
Cognitive and Meta Learning Strategies in Biomedical Research Healthcare examines the dynamic intersection of cognitive science and meta-learning within the realm of biomedical research. The book addresses how to overcome the complexities of contemporary health challenges by harnessing the power of advanced learning methodologies, such as cognitive processes and meta learning
- Includes self-contained chapters that detail literature reviews of cognitive meta learning in biomedical research
- Demonstrates the benefits of implementing AI based models in biomedical research
- Shows how cognitive meta learning, AI models, and other emerging technologies helps the healthcare sector
Computer scientists, biomedical engineers, and healthcare professionals interested in meta learning, cognitive informatics, AI and bioinformatics
1. Cognitive adaptation in biomedical informatics through meta learning strategies
2. Exploring neural networks in cognitive approach to biomedical data analysis and interpretation
3. Meta learning frameworks for precision medicine research
4. Harnessing meta learning for robust health solutions
5. Cognitive meta learning techniques for uncovering hidden patterns in biomedical information
6. Cognitive dynamics in drug discovery for accelerated biomedical breakthroughs
7. Integrating meta learning into biomedical diagnostics
8. Biomedical imaging through a cognitive and meta learning techniques
9. Meta reinforcement learning in health informatics
10. Cognitive internet of medical things
11. Meta cognitive neural networks based AI models for disease prediction
12. Cognitive meta learning based AI models for improved detection of neuropathology
13. Cognitive meta learning based AI models for neuro imaging
14. Cognitive meta learning based AI models for multimodal signals
15. Cognitive meta learning based AI models for clinical risk prediction with EHR
2. Exploring neural networks in cognitive approach to biomedical data analysis and interpretation
3. Meta learning frameworks for precision medicine research
4. Harnessing meta learning for robust health solutions
5. Cognitive meta learning techniques for uncovering hidden patterns in biomedical information
6. Cognitive dynamics in drug discovery for accelerated biomedical breakthroughs
7. Integrating meta learning into biomedical diagnostics
8. Biomedical imaging through a cognitive and meta learning techniques
9. Meta reinforcement learning in health informatics
10. Cognitive internet of medical things
11. Meta cognitive neural networks based AI models for disease prediction
12. Cognitive meta learning based AI models for improved detection of neuropathology
13. Cognitive meta learning based AI models for neuro imaging
14. Cognitive meta learning based AI models for multimodal signals
15. Cognitive meta learning based AI models for clinical risk prediction with EHR
- Edition: 1
- Published: March 1, 2026
- Language: English
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Subhendu Kumar Pani
Subhendu Kumar Pani received his Ph.D. from Utkal University Odisha, India. He has more than 16 years of teaching and research experience. His research interests include data mining, big data analysis, web data analytics, fuzzy decision making and computational intelligence. He is a fellow in SSARSC and life member in IE, ISTE, ISCA, OBA.OMS, SMIACSIT, SMUACEE, CSI.
Affiliations and expertise
Department of Computer Science and Engineering, Krupajal Engineering College, Bhubaneswar, Odisha, IndiaCC
Chinmay Chakraborty
Chinmay Chakraborty is an Assistant Professor (Sr.) in the Dept. of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, India. His main research interests include the Internet of Medical Things, Wireless Body Area Network, Wireless Networks, Telemedicine, m-Health/e-health, and Medical Imaging. He is an Editorial Board Member of various different journals and conferences
Affiliations and expertise
Assistant Professor Department of Electronics and Communication Engineering Birla Institute of Technology, Mesra, Jharkhand, IndiaSB
Sayonara Barbosa
Dr. Sayonara F. F. Barbosa is a Professor at the University of Cincinnati, USA. Professor Barbosa is a member of the Editorial Board of the International Journal of Medica Informatics and the Journal of Nursing Scholarship. From 2016 to 2020, at the International Medical Informatics Association, she was Vice-Chair of Nursing Informatics Special Interest Group, Brazil Representative. Her experience includes nursing in intensive care and information technology in healthcare, health information technology, healthcare technology, patient safety and donation of organs and transplants
Affiliations and expertise
Professor, University of Cincinnati, USA