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ScAN: Suicide Attempt and Ideation Events Dataset by Rawat, Bhanu Pratap Singh; Kovaly, Samuel; Pigeon, Wilfred R.; Yu, Hong is a scholarly article available to read on EtoBox.

What is ScAN: Suicide Attempt and Ideation Events Dataset about?

Suicide is an important public health concern and one of the leading causes of death worldwide. Suicidal behaviors, including suicide attempts (SA) and suicide ideations (SI), are leading risk factors for death by suicide. Information related to patients' previous and current SA and SI are frequently documented in the electronic health record (EHR) notes. Accurate detection of such documentation may help improve surveillance and predictions of patients' suicidal behaviors and alert medical professionals for suicide prevention efforts. In this study, we first built Suicide Attempt and Ideation Events (ScAN) dataset, a subset of the publicly available MIMIC III dataset spanning over 12k+ EHR notes with 19k+ annotated SA and SI events information. The annotations also contain attributes such as method of suicide attempt. We also provide a strong baseline model ScANER (Suicide Attempt and Ideation Events Retriever), a multi-task RoBERTa-based model with a retrieval module to extract all the relevant suicidal behavioral evidences from EHR notes of an hospital-stay and, and a prediction module to identify the type of suicidal behavior (SA and SI) concluded during the patient's stay at th

Author

Rawat, Bhanu Pratap Singh; Kovaly, Samuel; Pigeon, Wilfred R.; Yu, Hong

Published

2022

Language

EN