AI Podcast: How AI Can Improve the Diagnosis and Treatment of Diseases
Here’s a health care trend: we’re not going to live forever.
Data-driven medicine promises to pick out much more subtle trends — patterns that may only be apparent when you can compare the health care histories of tens of thousands of patients.
Patterns that can drive much more effective treatments.
As a result, medicine — particularly radiology and pathology — has become more data-driven. The Center for Clinical Data Science at Massachusetts General Hospital — led by Mark Michalski — promises to accelerate that, using AI technologies to spot patterns that can improve the detection, diagnosis and treatment of diseases.
“It’s not just about big data analytics, and it’s not just about genomics. It’s about the application of machine learning to suss up very valuable signals in places where you wouldn’t otherwise find it,” Michalski said in a conversation with tech journalist Michael Copeland in the latest episode of our AI Podcast.
Michalski outlined the changes he sees AI bringing to healthcare. They include not just more personalized medicine, but improved doctor-patient relationships as well.
“I think that for us to do our jobs well, as radiologists, is to serve our patients well,” Michalski said. “We have to start thinking in these terms. We are purveyors of data and we have to know how to hold that data, how to interpret that data.”
How a Computer Scientist Uses AI to Read Lost Literature
And if you missed our podcast last week, it’s worth a listen: Brent Seales, a computer scientist at the University of Kentucky, spoke about how he used AI to read some of the oldest pieces of literature in the world.
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