Evaluation of an artificial intelligence-based medical device for diagnosis of autism spectrum disorder
This is a virtual seminar. For a Zoom link, please see "Venue details". Please consider subscribing to mailing list: web.maillist.ox.ac.uk/ox/subscribe/ai4mch
Autism spectrum disorder (ASD) can be reliably diagnosed at 18 months, yet significant diagnostic delays persist in the United States. This double-blinded, multi-site, prospective, active comparator cohort study tested the accuracy of an artificial intelligence-based Software as a Medical Device designed to aid primary care healthcare providers (HCPs) in diagnosing ASD. The Device combines behavioral features from three distinct inputs (a caregiver questionnaire, analysis of two short home videos, and an HCP questionnaire) in a gradient boosted decision tree machine learning algorithm to produce either an ASD positive, ASD negative, or indeterminate output. This study compared Device outputs to diagnostic agreement by two or more independent specialists in a cohort of 18–72-month-olds with developmental delay concerns. The Device shows promise to significantly increase the number of children able to be diagnosed with ASD in a primary care setting, potentially facilitating earlier intervention and more efficient use of specialist resources.
Date: 28 February 2023, 15:00
Venue: https://us06web.zoom.us/j/86593859524?pwd=OThwZnZGSUlIY2NKekxDWXpiZmtQZz09
Speaker: Professor Sharief Taraman (University of California, Irvine School of Medicine / Cognoa Inc., Palo Alto)
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/info/ai4mch
Booking email: andrey.kormilitzin@psych.ox.ac.uk
Audience: Members of the University only
Editor: Andrey Kormilitzin