We also use language modeling, medical entity recognition, and normalization and negation detection to create a dataset of 2181 redditors that have discussed or implied suicidal ideation, behavior, or attempt. Our approach involves developing a suicide risk severity lexicon using medical knowledge bases and suicide ontology to detect cues relevant to suicidal thoughts and actions. We provide details of our learning framework that incorporates domain-specific knowledge to predict the severity of suicide risk for an individual. Our interdisciplinary study concerns the use of Reddit as an unobtrusive data source for gleaning information about suicidal tendencies and other related mental health conditions afflicting depressed users. PHQ-9) for suicide risk prediction failed to provide a quantitative assessment of risk that informed timely clinical decision-making for intervention.
This is particularly true for teenagers and younger adults where suicide is the second highest cause of death in the US Prior research involving surveys and questionnaires (e.g. While multiple initiatives have been developed and implemented for suicide prevention, a key challenge has been the social stigma associated with mental disorders, which deters patients from seeking help or sharing their experiences directly with others including clinicians. A report by Substance Abuse and Mental Health Services Administration (SAMHSA) shows that 80% of the patients suffering from Borderline Personality Disorder (BPD) have suicidal behavior, 5-10% of whom commit suicide. Mental health illness such as depression is a significant risk factor for suicide ideation, behaviors, and attempts. Knowledge-aware Assessment of Severity of Suicide Risk for Early Intervention
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