Kundu, A., Chaiton, M., Billington, R., Grace, D., Fu, R., Logie, C., Baskerville, N., Yager, C., Mitsakakis, N., & Schwartz, R. (2021). Machine learning applications in mental health and substance use research among lesbian, gay, bisexual, transgender, queer or questioning and two-spirit population: Scoping review (Preprint). JMIR Preprints. https://doi.org/10.2196/preprints.28962
Background: People at high risk of mental health or substance addiction issues among sexual and gender minorities may have
more nuanced characteristics that may not be easily discovered by traditional statistical methods.
Objective: This review aimed at identifying literature that used machine learning to investigate mental health or substance use
concerns among lesbian, gay, bisexual, transgender, queer or questioning and two-spirit (LGBTQ2S+) population as well as
directing future research in this field.