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Cognitive and Meta Learning Strategies in Biomedical Research and Healthcare [Minkštas viršelis]

Edited by (Department of Computer Science and Engineering, Krupajal Engineering College, Bhubaneswar, Odisha, India), Edited by (Assistant Professor Department of Electronics and Communication Engineering Birla Institute of Technology, Mesra, Jharkhand, In), Edited by
  • Formatas: Paperback / softback, 500 pages, aukštis x plotis: 229x152 mm
  • Išleidimo metai: 01-Oct-2025
  • Leidėjas: Academic Press Inc
  • ISBN-10: 0443403791
  • ISBN-13: 9780443403798
Kitos knygos pagal šią temą:
Cognitive and Meta Learning Strategies in Biomedical Research and Healthcare
  • Formatas: Paperback / softback, 500 pages, aukštis x plotis: 229x152 mm
  • Išleidimo metai: 01-Oct-2025
  • Leidėjas: Academic Press Inc
  • ISBN-10: 0443403791
  • ISBN-13: 9780443403798
Kitos knygos pagal šią temą:
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. It 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
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
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. 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 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