Podcast: Can we reduce medical error with artificial intelligence?
AI Improves Healthcare Access in Underserved Areas
Can we reduce medical errors with artificial intelligence? That question was recently addressed by Ferrum Health CEO, Pelu Tran, and Dr. John Banja, professor at the Center for Ethics at Emory University, during an episode of the ‘AI, Ethics and Radiology’ podcast series.
In his series, Dr. Banja examines the application of artificial intelligence in radiology. He and his guests discuss the ethical challenges AI presents and explore ways AI can assist and support healthcare professionals. They discuss everything from improving workflow to reducing the various kinds of errors that occur in contemporary healthcare delivery.
PODCAST: On Reducing Error in Clinical Care with Artificial Intelligence
May 12, 2022
Underserved populations often experience the highest rate of medical error. Improving both the quality of care and access to care can address this issue. The question becomes how do we efficiently and economically improve care for all patients regardless of socioeconomic status, resources, or location?
Pelu Tran outlines why AI is an effective way to improve access to quality healthcare.
“Technology is much cheaper. It’s much more scalable. You don’t need to hire radiologists to move to North Dakota to be able to improve quality care there. You just need to have electricity and GPUs with algorithms. I think just by definition, by making quality cheaper, more measurable, and frankly, much more powerful, you will just naturally start to expand.”
“AI technology has this fortunate tendency to become commoditized and cheaper for us as an open platform. We would love nothing more than to make sure we’re constantly finding the most cost-effective solutions.”
Alex uy
Alex is a recent UC San Diego graduate with a degree in economics and communications. His focus is digital marketing, and he has a passion for technology driven healthcare solutions.