Cognitive and Meta Learning Strategies in Biomedical Research and Healthcare

著者名：Chakraborty PhD, Chinmay (EDT)/Kumar Pani, Subhendu (EDT)/Barbosa PhD, Sayonara (EDT)

Academic Press（2026/02/27発売）

• 言語：ENG
• ISBN：9780443403798
• eISBN：9780443403804

Description

Cognitive and Meta Learning Strategies in Biomedical Research and 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.- Includes self-contained chapters, which include a detailed literature review of cognitive meta learning in biomedical research.- Demonstrate 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.

Table of Contents

1. Smartphone-based Human Activity Recognition for Healthcare Service with Meta Learning2. Cognitive Meta Learning-Based AI Models for Improved Detection of Neuropathology3. Revolutionising Brain Tumour Detection: Integrating AI and Machine Learning for Enhanced Diagnostic Accuracy and Healthcare Efficiency4. Integrating meta-learning into Biomedical Diagnostics5. Meta Reinforcement Learning in Health Informatics: A Meta Reinforcement Learning Framework for Blood Glucose Level Control in Type 1 Diabetes6. Cognitive Meta-Learning Techniques for Uncovering Hidden Patterns in protein Information: A Gender-Based Analysis of Undergraduate Biochemistry Students in Pakistan7. Hip Exoskeleton Controller Design: A Comprehensive Review for People with Leg Deformities8. Explainable AI for Epileptic Neonatal EEG Classification9. An AI-enabled Meta Learning Approach towards Prediction of Cardiological Disorders in Healthcare Sector10. Cognitive Meta Learning-based AI models for Multimodal Signals11. Cognitive Meta-Learning Techniques for Uncovering Hidden Patterns in Biomedical Information12. A Cognitive Learning Approach for Severity Classification of Diabetic Retinopathy Using Voting Based Selection of Deep Models13. Challenges and Mitigating Strategies for AI based Meta Learning with Multimodal signals14. Revolutionizing Healthcare with the Cognitive Internet of Medical Things: AI-Driven Connectivity and Smart Systems for Personalized Care