Machine learning algorithms can help predict mental health issues in employees by analyzing data from mental health surveys. Researchers used supervised learning algorithms like support vector machines, logistic regression, k-nearest neighbors, decision trees and random forest on survey data from tech and non-tech companies. Key factors identified for predicting mental disorders included whether the employee worked at a tech company, their age, gender, family history of mental health issues, personal history, and whether they discussed mental health with their employer. Related studies used logistic models and smartphones to predict anxiety disorders and monitor bipolar disorder.