Book chapter
Aifred Health, a Deep Learning Powered Clinical Decision Support System for Mental Health
The NIPS '17 Competition:Building Intelligent Systems, pp.251-287
28/Sep/2018
Abstract
Aifred Health, one of the top two teams in the first round of the IBM Watson AI XPRIZE competition, is using deep learning to solve the problem of treatment selection and prognosis prediction in mental health, starting with depression. Globally, depression affects over 300 million people and is the leading cause of disability. While a range of effective treatments do exist, patients’ responses to treatments vary to a large degree. Some patients spend years going through a frustrating ‘trial-and-error’ process in order to find an effective treatment. The Aifred Health solution is a deep learning-powered Clinical Decision Support System (CDSS) aimed at helping clinicians select the most effective treatment plans for depression in collaboration with their patients. In this chapter, we discuss problem of treatment selection in depression and explore the technical, clinical, and ethical dimensions of building a CDSS for mental health based on deep learning technology.
Details
- Title
- Aifred Health, a Deep Learning Powered Clinical Decision Support System for Mental Health
- Creators
- David David Benrimoh (null) - McGill UniversityRobert Fratila (null) - Aifred Health (Canada, Montreal)Sonia Israel (null) - Aifred Health (Canada, Montreal)Kelly Perlman (null) - McGill UniversityNykan Mirchi (null) - McGill UniversitySneha Desai (null) - McGill UniversityAriel Rosenfeld (null) - 972WIS_INST___83Sabrina Knappe (null) - McGill UniversityJason Behrmann (null) - McGill UniversityColleen Rollins (null) - McGill UniversityRaymond Penh You (null) - McGill University
- Resource Type
- Book chapter
- Publication Details
- The NIPS '17 Competition:Building Intelligent Systems, pp.251-287
- Chapter Number
- Book Chapter: 13
- Number of pages
- 37
- Book Editors
- Escalera, Sergio ; Weimer, Markus
- Series
- The Springer Series on Challenges in Machine Learning
- Publisher
- Springer Verlag
- Language
- English
- DOI
- https://doi.org/10.1007/978-3-319-94042-7
- Grant note
- NA
- ISBN
- 978-3-319-94041-0
- Record Identifier
- 993267854903596
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