AI is transforming radiology, but not at the expense of skilled technicians. In the same way that personal computers and spreadsheets didn’t eliminate accountants, AI is not going to replace radiologists but will instead transform the way they work. 
 
MIT CSAIL Professor Polina Golland’s research sits at the intersection of machine learning and healthcare, specifically medical imaging. In this episode, she discusses her team’s groundbreaking work on algorithms that analyze subtle patterns in x-rays, helping detect diseases earlier and understand them more deeply.
 
This conversation covers:
 
2:00 - How do doctors diagnose heart failure?
5:27 - Converting medical imagery to numbers
8:20 - Code generation for radiologists
9:25 - Weaknesses in the medical system that computing can strengthen
16:48 - The choreography of treating a patient
20:31 -  Turning an algorithm into a product
24:26 - Will radiologists be replaced by AI?
30:21 - How will AI change medical imagery?
 
Connect with CSAIL Alliances:
On our site: cap.csail.mit.edu/about-us/meet-our-team
On LinkedIn: linkedin.com/company/mit-csail #MITCSAIL #AI #GenerativeAI #Leadership #Technology #CSAILPodcast

How AI is Reshaping Medical Imagery with MIT CSAIL Professor Polina Golland

MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) Alliances serves as a gateway into the lab for industry and governmental institutions seeking a closer connection to the work, researchers, and students of CSAIL. Our podcast aims to provide inside access to topics covered by CSAIL and other leaders advancing computer science and AI research.

How AI is Reshaping Medical Imagery with MIT CSAIL Professor Polina Golland

MIT CSAIL Alliances