An Iterative and Collaborative End-to-End Methodology Applied to Digital Mental Health

An Iterative and Collaborative End-to-End Methodology Applied to Digital Mental Health

Artificial intelligence (AI) algorithms together with advances in data storage have recently made it possible to better characterize, predict, prevent, and treat a range of psychiatric illnesses. Amid the rapidly growing number of biological devices and the exponential accumulation of data in the me...

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Bibliographic Details
Main Authors: Laura Joy Boulos, Alexandre Mendes, Alexandra Delmas, Ikram Chraibi Kaadoud
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Psychiatry
Subjects:
digital mental health
an end-to-end methodology
human factors
cognitive biases
machine learning
knowledge discovery data base (KDD)
Online Access:https://www.frontiersin.org/articles/10.3389/fpsyt.2021.574440/full

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https://www.frontiersin.org/articles/10.3389/fpsyt.2021.574440/full

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