Objective Instruments rating risk of harm to self and others are widely used in inpatient
forensic psychiatry settings. A potential alternate or supplementary means of risk prediction …

Background Using novel data mining methods such as natural language processing (NLP)
on electronic health records (EHRs) for screening and detecting individuals at risk for …

Objective This paper evaluates the application of a natural language processing (NLP)
model for extracting clinical text referring to interpersonal violence using electronic health …

BackgroundThis study evaluated whether natural language processing (NLP) of
psychotherapy note text provides additional accuracy over and above currently used suicide …

Background Suicide is a serious public health issue, accounting for 1.4% of all deaths
worldwide. Current risk assessment tools are reported as performing little better than chance …

Background Emergency departments (ED) are an important intercept point for identifying
suicide risk and connecting patients to care, however, more innovative, person-centered …

Background Social risk factors are important dimensions of health and are linked to access
to care, quality of life, health outcomes and life expectancy. However, in the Electronic …

Natural language processing (NLP) and machine learning were used to predict suicidal
ideation and heightened psychiatric symptoms among adults recently discharged from …

Machine learning techniques are increasingly being applied to clinical text that is already
captured in the Electronic Health Record for the sake of delivering quality care. Applications …

Introduction School violence has a far-reaching effect, impacting the entire school
population including staff, students and their families. Among youth attending the most …