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Episode 34: ACM-AMIA Joint Podcast Series: Clinical AI-Challenges and Advice

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Manage episode 379581723 series 3379826
Indhold leveret af AMIA. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af AMIA eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Hosts: Sabrina Hsueh PhD Adela Grando, PhD

Guest: Regina Barzilay, School of Engineering Distinguished Professor of AI & Health in the Department of Computer Science at the Massachusetts Institute of Technology and the AI Faculty Lead at MIG Jameel Clinic

In this episode, part of a special collaboration between ACM ByteCast and the American Medical Informatics Association (AMIA)’s For Your Informatics podcast, hosts Sabrina Hsueh and Adela Grando welcome Regina Barzilay, a School of Engineering Distinguished Professor of AI & Health in the Department of Computer Science at the Massachusetts Institute of Technology and the AI Faculty Lead at MIT Jameel Clinic. She develops machine learning methods for drug discovery and clinical AI. In the past, she worked on natural language processing. Her research has been recognized with the MacArthur Fellowship, an NSF Career Award, and the AAAI Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity. Regina is a member of the National Academy of Engineering and American Academy of Arts and Sciences. Regina describes her career journey, and how a personal experience with the healthcare system led her to work on an AI-based system for the early detection—and prediction of—breast cancer. She explains why entering the interdisciplinary field of clinical AI is so challenging and offers valuable advice on how to overcome some of these challenges. Regina also opines on new models for using AI, including the promise of ChatGPT in healthcare. Finally, she talks about inequity in medicine, and offers actionable insights on how to mitigate these shortfalls while moving the field of clinical AI forward.

  continue reading

41 episoder

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Manage episode 379581723 series 3379826
Indhold leveret af AMIA. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af AMIA eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Hosts: Sabrina Hsueh PhD Adela Grando, PhD

Guest: Regina Barzilay, School of Engineering Distinguished Professor of AI & Health in the Department of Computer Science at the Massachusetts Institute of Technology and the AI Faculty Lead at MIG Jameel Clinic

In this episode, part of a special collaboration between ACM ByteCast and the American Medical Informatics Association (AMIA)’s For Your Informatics podcast, hosts Sabrina Hsueh and Adela Grando welcome Regina Barzilay, a School of Engineering Distinguished Professor of AI & Health in the Department of Computer Science at the Massachusetts Institute of Technology and the AI Faculty Lead at MIT Jameel Clinic. She develops machine learning methods for drug discovery and clinical AI. In the past, she worked on natural language processing. Her research has been recognized with the MacArthur Fellowship, an NSF Career Award, and the AAAI Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity. Regina is a member of the National Academy of Engineering and American Academy of Arts and Sciences. Regina describes her career journey, and how a personal experience with the healthcare system led her to work on an AI-based system for the early detection—and prediction of—breast cancer. She explains why entering the interdisciplinary field of clinical AI is so challenging and offers valuable advice on how to overcome some of these challenges. Regina also opines on new models for using AI, including the promise of ChatGPT in healthcare. Finally, she talks about inequity in medicine, and offers actionable insights on how to mitigate these shortfalls while moving the field of clinical AI forward.

  continue reading

41 episoder

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