Machine Learning for Health (ML4H): What are important considerations to build tools that solve clinical problems? A brainstorming session with clinicians.
Activity: Talk or presentation types › Invited talk
Description
Machine learning for health research is often criticized for missing the mark when it comes to clinically meaningful endpoints. Critics argue that research on novelty tasks or datasets does little to improve patient outcomes. In this roundtable we aim to discern what parameters and considerations should go into better selecting important clinical problems.