AI for Biomedical Research Volume 1

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 impacts.Key FeaturesThis book is the only resource covering AI applications across the entire research journey, from initial idea through long-term impactIt 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 practiceIt includes detailed analysis of the EU AI Act implementation timeline (February 2025 through August 2027) with specific guidance for research applications. It helps researchers and institutions understand high-risk classifications, research exemptions, and compliance strategies before requirements take effectIt 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 limitationsThis 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 resourcesVolume 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 resultsVolume 2 continues the exploration of quality assurance, dissemination, peer review, impact, and the necessary institutional changes to responsibly implement AI capabilities