reviewTop 1% cited
Machine learning in mental health: a scoping review of methods and applications
Psychological Medicine · 2019 · Vol. 49(09) · pp. 1426–1448
Adrian Shatte✉(Federation University)Delyse Hutchinson(Royal Children's Hospital)Samantha Teague(Deakin University)
Abstract
Overall, the application of ML to mental health has demonstrated a range of benefits across the areas of diagnosis, treatment and support, research, and clinical administration. With the majority of studies identified focusing on the detection and diagnosis of mental health conditions, it is evident that there is significant room for the application of ML to other areas of psychology and mental health. The challenges of using ML techniques are discussed, as well as opportunities to improve and advance the field.
Mental Health via WritingMental Health Research TopicsDigital Mental Health InterventionsMental healthLatent Dirichlet allocationBig dataMachine learningPsychologySupport vector machineClinical decision support systemField (mathematics)Applied psychologyArtificial intelligence
MeSH terms
Machine LearningMental DisordersHumansMental HealthPublic Health
Citations
907
FWCI
94.75
field-weighted impact
References
343
Percentile
100%
vs. same field & year
Citations per year
References
Machine learning: Trends, perspectives, and prospects
Science · 2015 · 9,250 citations
Harnessing Context Sensing to Develop a Mobile Intervention for Depression
Journal of Medical Internet Research · 2011 · 673 citations
Citation Network
How this paper connects to the literature. Drag to explore, click any node to open that paper.
