AI Medical Compendium Journal:
Suicide & life-threatening behavior

Showing 1 to 5 of 5 articles

Predicting suicide risk in real-time crisis hotline chats integrating machine learning with psychological factors: Exploring the black box.

Suicide & life-threatening behavior
BACKGROUND: This study addresses the suicide risk predicting challenge by exploring the predictive ability of machine learning (ML) models integrated with theory-driven psychological risk factors in real-time crisis hotline chats. More importantly, w...

A Machine Learning Approach to Identifying the Thought Markers of Suicidal Subjects: A Prospective Multicenter Trial.

Suicide & life-threatening behavior
Death by suicide demonstrates profound personal suffering and societal failure. While basic sciences provide the opportunity to understand biological markers related to suicide, computer science provides opportunities to understand suicide thought ma...

Analysis of NTSB Aircraft-Assisted Pilot Suicides: 1982-2014.

Suicide & life-threatening behavior
On March 24, 2015, a Germanwings aircraft crashed in the Alps. The suicidal copilot killed himself and 150 others. Pilot suicide is rare, but does happen. This research analyzed the National Transportation Safety Board's accident database (eADMS) loo...

A Controlled Trial Using Natural Language Processing to Examine the Language of Suicidal Adolescents in the Emergency Department.

Suicide & life-threatening behavior
What adolescents say when they think about or attempt suicide influences the medical care they receive. Mental health professionals use teenagers' words, actions, and gestures to gain insight into their emotional state and to prescribe what they beli...

Computing 3-Step Theory of Suicide Factor Scores From Veterans Health Administration Clinical Progress Notes.

Suicide & life-threatening behavior
BACKGROUND: Literature on how to translate information extracted from clinical progress notes into numeric scores for 3-step theory of suicide (3ST) factors is nonexistent. We determined which scoring option would best discriminate between patients w...