Large language models for data-driven insights from real-world health data
This is a virtual seminar. For a Zoom link, please see "Venue" section. Please consider subscribing to mailing list: web.maillist.ox.ac.uk/ox/subscribe/ai4mch
With rapid developments in the field of artificial intelligence and large language models in healthcare, the need for thoughtful, ethical, impactful applications is imperative. This webinar will explore the potential – and perils – of large language models to unlock new insights from the electronic health records to provide more personalized care while reducing clinician work burden. Dr. Bitterman will discuss her research in large language models for extracting information from clinical documentation, including social determinants of health. She will discuss ethical considerations of large language models for healthcare, including future directions for more robust reporting and evaluation standards.
Date:
21 May 2024, 15:00 (Tuesday, 5th week, Trinity 2024)
Venue:
https://zoom.us/j/91092603798?pwd=NUxQVGZ0SzY4OUR1TzRDOW9SdGQ2dz09
Speaker:
Dr Danielle S. Bitterman (Harvard Medical School)
Organising department:
Department of Psychiatry
Organiser:
Dr Andrey Kormilitzin (University of Oxford)
Organiser contact email address:
andrey.kormilitzin@psych.ox.ac.uk
Host:
Dr Andrey Kormilitzin (University of Oxford)
Part of:
Artificial Intelligence for Mental Health Seminar Series
Booking required?:
Not required
Booking url:
https://web.maillist.ox.ac.uk/ox/subscribe/ai4mch
Booking email:
andrey.kormilitzin@psych.ox.ac.uk
Audience:
Public
Editor:
Andrey Kormilitzin
