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
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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
Me, Myself, and AI: Building Better Answers With AI Agents, featuring SAP’s Walter Sun (Bonus Episode!)
CSAIL Alliances Podcasts
25 minutes 46 seconds
4 weeks ago
Me, Myself, and AI: Building Better Answers With AI Agents, featuring SAP’s Walter Sun (Bonus Episode!)
In this special crossover episode, we're bringing you a conversation from our friends at Me, Myself, and AI, a podcast by MIT Sloan Management Review and Boston Consulting Group.
Walter Sun, Senior VP and Global Head of AI at SAP, joins hosts Shervin Khodabandeh and Sam Ransbotham for a deep dive into how SAP is deploying AI at scale across its platforms, from building a generative AI hub with access to over 30 large language models to developing specialized AI agents that reduce hallucinations.
You’ll hear insights into:
The real-world use of small vs. large language models
How SAP is empowering employees through “AI Days”
What AI agents can teach us about specialization and collaboration
How to avoid hallucinations with fine-tuned, task-specific agents
Building trust and transparency into enterprise AI systems
Whether you're an AI enthusiast, enterprise leader, or just curious about how cutting-edge AI is transforming business, hear how AI is shaping industry strategy and transforming the market.
For more episodes from Me, Myself, and AI: https://sloanreview.mit.edu/audio-series/me-myself-and-ai/
Connect with CSAIL Alliances:
On our site: https://cap.csail.mit.edu/
On LinkedIn: https://www.linkedin.com/company/mit-csail/
CSAIL Alliances Podcasts
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
