High-quality data is the cornerstone of effective machine learning in healthcare. This talk presents practical strategies and emerging techniques for managing medical imaging datasets, from synthetic data generation and curation to evaluation and deployment.

We’ll begin by highlighting real-world case studies from leading researchers and practitioners who are reshaping medical imaging workflows through data-centric practices. The session will then transition into a hands-on tutorial using FiftyOne, the open-source platform for visual dataset inspection and model evaluation. Attendees will learn how to load, visualize, curate, and evaluate medical datasets across various imaging modalities.

Whether you're a researcher, clinician, or ML engineer, this talk will equip you with practical tools and insights to improve dataset quality, model reliability, and clinical impact.