Comparisons of different classification algorithms while using text mining to screen psychiatric inpatients with suicidal behaviors

ConclusionThis study confirmed the feasibility of filtering suicidal inpatients with small amounts of representative terms. SVM, Random Forest and AdaBoost weighted by TF have better performance in this task. Our findings provided a practical way to automatically classify patients with or without suicidal behaviors before admission to hospital, which potentially led to considerable savings in time and human resources for identification of high-risk patients and suicide prevention.
Source: Journal of Psychiatric Research - Category: Psychiatry Source Type: research