AI for Biomedical Research: Volume 1: From Idea to Analysis

Description

Artificial intelligence 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 artificial intelligence across the complete research lifecycle, from initial ideation through... Read more

Artificial intelligence 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 artificial intelligence across the complete research lifecycle, from initial ideation through analysis, quality assurance, dissemination, and long-term impact.

Key Features

The only resource covering AI applications across the entire research journey, from initial idea through long-term impact.
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.
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.
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.
The book will feature 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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The Challenge of Reviewing AI in Research
Healthcare AI Governance Frameworks
Algorithm Transparency and Explainability
Bias, Fairness, and Equity Assessment
Safety, Validation, and Performance Evaluation
Informed Consent for AI-Enabled Research
Privacy, Data Protection, and Security
Regulatory Classification and Oversight
Continuous Learning and Adaptive Systems
Adverse Event Reporting and Learning Systems
AI in Animal Research: IACUC Considerations
Practical Guidance for IRBs and IACUCs
Current Challenges and Future Directions

Part IV: Research Execution

Chapter 11: Participant Recruitment and Engagement

The Challenge of Participant Recruitment
AI for Eligibility Screening
Recruitment Optimization
Participant Engagement and Retention
Capabilities and Limitations
Ethical Considerations
Practical Implementation Strategies
Future Directions

Chapter 12: Research Operations and Project Management

The Challenge of Research Operations
Timeline and Schedule Optimization
Resource Allocation and Optimization
Risk Management and Mitigation
Communication and Collaboration Support
Data Quality Monitoring and Management
Progress Tracking and Reporting
Change Management and Adaptation
Technology Integration and Management
Capabilities and Limitations
Ethical Considerations
Practical Implementation Strategies
Future Directions

Part V: Data and Analysis

Chapter 13: Data Collection and Management

The Challenge of Research Data in the AI Era
Foundational Frameworks for AI in Data Management
AI-Enhanced Data Collection
AI-Powered Data Management
Data Quality Assurance with AI
Synthetic Data Generation
Data Governance and Stewardship
Capabilities and Limitations
Ethical Considerations
Practical Implementation Strategies
Future Directions

Chapter 14: Data Analysis and Interpretation

The Challenge of Modern Research Data Analysis
Foundational Frameworks for AI Analysis
AI for Exploratory Data Analysis
Statistical Analysis and Hypothesis Testing
Predictive Modeling and Machine Learning
Deep Learning Applications
Interpretability and Explainability
Causal Inference
Robustness and Reliability
Uncertainty Quantification
Capabilities and Limitations
Ethical Considerations
Practical Implementation Strategies
Future Directions

Epilogue: From Analysis to Impact

The Journey So Far
What Analysis Reveals and What Remains
The Companion Volume
Principles for the AI-Enhanced Researcher
Looking Forward

Notes

Index

Author(s)

Biography

Molly Klote, MD, is the former Director of the US Department of Health and Human Services Office for Human Research Protections (OHRP). OHRP is the policy, education, and compliance office that oversees federally funded medical research for 21 federal agencies, 13,000 institutions, and over 6000 institutional review boards in the US and internationally. It is the proponent office for the policy known as "The Common Rule" (45 CFR 46). Before joining OHRP, Dr. Klote spent six years as the research policy, regulatory, and education lead for the Veterans Health Administration, the largest integrated healthcare system in the United States. Prior to the Veterans Health Administration, she served for 30 years in the Army, with her final assignment at the rank of Colonel, working for the Army Surgeon General, overseeing all US Army Human Research policy and compliance. Additionally, Dr. Klote has directed two major research program offices, served as an Institutional Official, chaired three Institutional Review Boards, and led a Research Scientific Review Board. She recently launched her own consulting company, Klote Medical Research Advisors, LLC, to bring her over 36 years of distinguished military and civilian federal experience to those who need to better understand federal research policy. She is the author of Adapting to Change: Federal Policy Dynamics and the Pharmaceutical Industry, CRC Press 2025.

AI for Biomedical Research Volume 1: From Idea to Analysis

Description

Table of Contents

Author(s)

Biography

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