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Technology Matters: Machine learning approaches to personalised child and adolescent mental health care
Author(s) -
Paton Lewis W.,
Tiffin Paul A.
Publication year - 2022
Publication title -
child and adolescent mental health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.912
H-Index - 46
eISSN - 1475-3588
pISSN - 1475-357X
DOI - 10.1111/camh.12546
Subject(s) - mental health , context (archaeology) , task (project management) , key (lock) , computer science , health care , artificial intelligence , mental health care , psychology , machine learning , data science , applied psychology , psychiatry , computer security , engineering , systems engineering , paleontology , economics , biology , economic growth
There has been much interest in the potential for machine learning and artificial intelligence to enhance health care. In this article, we discuss the potential applications of the technology to child and adolescent mental health services (CAMHS). We also outline the four key criteria that are likely to be necessary for automated prediction to be translated into clinical benefit. These relate to the choice of task to be automated, the nature of the available data , the methods applied and the context of the system to be implemented.