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Can Open-Source LLMs Compete With Proprietary Ones for Complex Diagnoses?

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Manage episode 475212560 series 2965419
Content provided by American Medical Association and JAMA Network. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by American Medical Association and JAMA Network 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://ppacc.player.fm/legal.

A recent study published in JAMA Health Forum suggests that institutions may be able to deploy custom open-source large language models (LLMs) that run locally without sacrificing data privacy or flexibility. Coauthors Thomas A. Buckley, BS, and Arjun K. Manrai, PhD, from the Department of Biomedical Informatics at Harvard Medical School join JAMA+ AI Editor in Chief Roy H. Perlis, MD, MSc, to discuss. Related Content:

  continue reading

238 episodes

Artwork
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Manage episode 475212560 series 2965419
Content provided by American Medical Association and JAMA Network. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by American Medical Association and JAMA Network 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://ppacc.player.fm/legal.

A recent study published in JAMA Health Forum suggests that institutions may be able to deploy custom open-source large language models (LLMs) that run locally without sacrificing data privacy or flexibility. Coauthors Thomas A. Buckley, BS, and Arjun K. Manrai, PhD, from the Department of Biomedical Informatics at Harvard Medical School join JAMA+ AI Editor in Chief Roy H. Perlis, MD, MSc, to discuss. Related Content:

  continue reading

238 episodes

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