The Future of AI – Algorithms and Data Sets

This four-part, after-hours series introduces imaging informatics and its role in modern medicine, helping students and trainees understand how imaging data, technology, and clinical workflows come together to improve patient care, while also highlighting emerging innovations and potential career paths in the field. Register for each session separately. 

April 20 | Session 1

What is Clinical & Imaging Informatics

April 27 | Session 2

How Clinical Data Moves: The Infrastructure Behind Modern Imaging

May 4 | Session 3

The Imaging Lifecycle: Workflow, Bottlenecks, and Safety

May 11 | Session 4

The Future of AI – Algorithms and Data Sets

As interest in AI continues to grow across medicine, understanding how imaging data are built, governed, and translated into clinical applications has become increasingly important. We invite you to join the final conversation of an after-hours series focused on imaging informatics and its role in modern healthcare. Speakers will explore how high-quality, clinically meaningful datasets are developed and validated, examine governance and oversight considerations, and highlight how strong data foundations influence AI performance and support safe, effective integration into clinical workflows.

Objectives

1. Outline the steps required to construct a clinically meaningful imaging dataset 
2. Compare methods for extracting and linking imaging and clinical data 
3. Explain governance requirements, including IRB oversight and data use agreements 
4. Identify common pitfalls that compromise dataset validity and AI performance 
5. Evaluate key considerations for safe and effective AI integration into imaging workflows