Cox, C.R., Moscardini, E.H., Cohen, A.S. and Tucker, R.P. (2020) Machine Learning for Suicidology: A Practical Review of Exploratory and Hypothesis-Driven Approaches. Clinical Psychology Review, 82, Article ID: 101940.
https://doi.org/10.1016/j.cpr.2020.101940

has been cited by the following article:

• TITLE: Review on Psychology Research Based on Artificial Intelligence Methodologies

  AUTHORS: Rushit Dave, Kyle Sargeant, Monika Vanamala, Naeem Seliya

  KEYWORDS: Psychology, Mental Illness, Depression, Suicide, Self-Injury

  JOURNAL NAME: Journal of Computer and Communications, Vol.10 No.5, May 31, 2022

  ABSTRACT: The field of psychology and health care are often viewed as very different. One of the main differences between these two fields is the application of prediction. When it comes to physical health, the health care and the medical field can predict outcomes of an individual’s health based on things like diet, exercise, and genetic makeup. Psychology is a little bit different; psychologists are great at predicting behavioral changes in patients, but the prediction of an individual’s mental health is not up to par with the prediction of physical health in the medical field for several factors. The scope of this study is to highlight how artificial intelligence has been applied to the field of psychology. In particular, how machine learning and deep learning technologies have been used to predict developmental risks of mental health disorders and risk of suicidal/self-injurious behaviors, as well as how artificial intelligence can be used to detect levels of depression.