Advances in Non-imaging AI for Healthcare
As healthcare data are acquired in ever-growing quantities, new classes of AI algorithm are required to help humans understand and model these complex datasets, which now include recordings from millions of patients. This seminar will introduce new developments in the rapidly-growing field of (non-imaging) “Clinical AI”, demonstrating how data scientists can benefit from having “AI to help train the AI”; that is, machine learning networks involved in the construction of new machine learning networks. It will demonstrate successful projects that have been translated into healthcare practice, and highlight on-going international developments in the field, with examples from collaborative work between our lab and the Big Data Institute.

Link to join: teams.microsoft.com/l/meetup-join/19%3ameeting_OWU3ZmZhZDQtZTMyYS00ZWM4LWEyZDgtNzI2MmQyMDE1ZmIw%40thread.v2/0?context=%7b%22Tid%22%3a%22cc95de1b-97f5-4f93-b4ba-fe68b852cf91%22%2c%22Oid%22%3a%22023585af-48b7-481a-ba53-42b34afdbea1%22%7d
Date: 5 July 2021, 10:00 (Monday, 11th week, Trinity 2021)
Venue: Venue to be announced
Speaker: Professor David Clifton (Department of Engineering Science of the University of Oxford)
Organising department: Nuffield Department of Population Health
Organiser: Graham Bagley (University of Oxford, Nuffield Department of Population Health)
Part of: Population Health Seminars
Booking required?: Not required
Audience: Members of the University only
Editor: Hannah Freeman