Medical Datasets for AI Research: A Practical Guide for Healthcare Innovation (Health Innovation Toolbox)

This open-access guide provides a structured introduction to medical datasets for AI research, covering key data sources, types, standards, and real-world applications in healthcare innovation. Designed for students, healthcare professionals, and digital health innovators, it explains how clinical data fuels AI models, from data collection and quality assessment to ethical and regulatory considerations.

The guide highlights open medical datasets, tools, and frameworks used in machine learning workflows, while emphasizing the importance of data accuracy, diversity, and compliance in building safe and effective AI systems. It also explores how different data modalities, such as electronic health records, medical imaging, and genomic data, support various AI use cases in healthcare.

As part of the HealthInnovation Toolbox series, this resource aims to bridge the gap between foundational knowledge and practical implementation, enabling a broader community to engage with healthcare AI responsibly and effectively.