Avoiding Overfitting in Suicide Prediction Models

A new study highlights the dangers of overfitting in machine learning models used to predict suicidal ideation. The study argues that such models may be more likely to identify patterns in the data that are not actually related to suicidal ideation, leading to inaccurate predictions. The authors suggest that more research is needed to develop machine learning models that are better suited to predicting suicidal ideation and other mental health outcomes.