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Akshay Chaudhari: LLMs for Clinical Text Summarization

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Manage episode 413975951 series 2997170
Content provided by Anirban Mukhopadhyay, Henry Krumb, Anirban Mukhopadhyay, and Henry Krumb. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anirban Mukhopadhyay, Henry Krumb, Anirban Mukhopadhyay, and Henry Krumb 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://player.fm/legal.

Akshay Chaudhari is an Assistant Professor in the Integrative Biomedical Imaging Informatics at the Department of Radiology in Stanford University, USA. He leads the Machine Intelligence in Medical Imaging research group and has a primary research interest at the intersection of artificial intelligence and medical imaging. He also serves as the Associate Director of Research and Education at the Stanford AIMI Center. Adapted large language models can outperform medical experts in clinical text summarization

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73 episodes

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Manage episode 413975951 series 2997170
Content provided by Anirban Mukhopadhyay, Henry Krumb, Anirban Mukhopadhyay, and Henry Krumb. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anirban Mukhopadhyay, Henry Krumb, Anirban Mukhopadhyay, and Henry Krumb 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://player.fm/legal.

Akshay Chaudhari is an Assistant Professor in the Integrative Biomedical Imaging Informatics at the Department of Radiology in Stanford University, USA. He leads the Machine Intelligence in Medical Imaging research group and has a primary research interest at the intersection of artificial intelligence and medical imaging. He also serves as the Associate Director of Research and Education at the Stanford AIMI Center. Adapted large language models can outperform medical experts in clinical text summarization

  continue reading

73 episodes

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