A Path for Translation of Machine Learning Products into Healthcare Delivery

Summary

The biggest challenge in healthcare AI isn't developing algorithms—it's successfully translating research breakthroughs into operational clinical tools that deliver real-world impact in clinical care. Dr. Sendak and his colleagues at DIHI develop a translation framework that bridges this critical gap by providing the structured methodology that transforms promising AI research into practical solutions that integrate with clinical workflows, staff capabilities, and organizational ways of working.