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AI for Biomedical Research Volume 1: From Idea to Analysis
Paperback
Series: AI for Everything
Medical ReferenceTechnology & Engineering
ISBN13: 9781041323396
Publisher: CRC Press
Published: Nov 4 2026
Pages: 264
Language: English
Artificial intelligence (AI) is transforming every aspect of biomedical research practice. Researchers face a fragmented landscape of tools, evolving ethical requirements, emerging regulations, and rapidly shifting best practices. The first of two volumes, this book provides a comprehensive treatment of AI across the complete research lifecycle, from initial ideation through analysis, quality assurance, dissemination, and long-term impact.
Key Features
- This book is the only resource covering AI applications across the entire research journey, from initial idea through long-term impact.
- It systematically applies four major AI governance frameworks (RUAIH, FUTURE-AI, NIST AI RMF, and GMLP) throughout both volumes, showing researchers how to operationalize abstract principles in daily practice.
- It includes detailed analysis of the EU AI Act implementation timeline (February 2025 through August 2027) with specific guidance for research applications. Helps researchers and institutions understand high-risk classifications, research exemptions, and compliance strategies before requirements take effect.
- It moves beyond hype and fear to deliver a balanced, practical approach to human-AI collaboration. Each chapter includes Capabilities and Limitations analysis, ethical considerations, and implementation strategies that acknowledge both AI's transformative potential and its persistent limitations.
- This book features concrete examples demonstrating implementation principles in practice. Each chapter concludes with practical implementation strategies, reflection questions, and guidance applicable to institutions of varying sizes and resources.
- Volume 1 explores how AI can improve essential research activities, including designing studies, securing funding, navigating compliance and ethics reviews, recruiting participants, managing operations, collecting data, and analyzing results.
- Volume 2 continues the exploration of quality assurance, dissemination, peer review, impact, and the necessary institutional changes to responsibly implement AI capabilities.
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