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Google’s Efforts to Build Patient-Facing AI: A Conversation with Drs. Alan Karthikesalingam and Anil Palepu

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Manage episode 489500794 series 3464196
Content provided by NEJM Group. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by NEJM Group or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this episode of NEJM AI Grand Rounds, guests Drs. Alan Karthikesalingam and Anil Palepu of Google walk co-hosts Raj Manrai and Andy Beam through the making and evaluation of AMIE, an AI system designed to conduct clinical conversations with patients. Alan and Anil explain how AMIE was trained using synthetic doctor-patient interactions generated by LLMs playing multiple roles—doctor, patient, critic, and moderator. They reveal how synthetic dialogue, guided by structured feedback and grounded in search, proved more effective than noisy real-world transcripts in building a model that could reason, ask questions, and show empathy. The discussion also covers what the “long tail” of medicine demands for building robust AI systems and how AMIE might one day augment real clinical workflows. Finally, Alan reflects on how AI has changed—and how it hasn’t—in the two years since he was last on the podcast.

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33 episodes

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Manage episode 489500794 series 3464196
Content provided by NEJM Group. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by NEJM Group or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this episode of NEJM AI Grand Rounds, guests Drs. Alan Karthikesalingam and Anil Palepu of Google walk co-hosts Raj Manrai and Andy Beam through the making and evaluation of AMIE, an AI system designed to conduct clinical conversations with patients. Alan and Anil explain how AMIE was trained using synthetic doctor-patient interactions generated by LLMs playing multiple roles—doctor, patient, critic, and moderator. They reveal how synthetic dialogue, guided by structured feedback and grounded in search, proved more effective than noisy real-world transcripts in building a model that could reason, ask questions, and show empathy. The discussion also covers what the “long tail” of medicine demands for building robust AI systems and how AMIE might one day augment real clinical workflows. Finally, Alan reflects on how AI has changed—and how it hasn’t—in the two years since he was last on the podcast.

Transcript.

  continue reading

33 episodes

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