Methods for Identifying Suicide or Suicidal Ideation in EHRs

By Krystl Haerian, H. Salmasian, Carol Friedman. 2012

80 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Zexian Zeng
2. Yuan Luo
3. Yu Deng
4. Xiaoyu Li
5. Tristan Naumann
6. Hong Yu
7. Abhyuday N. Jagannatha
8. Janyce Wiebe

Citations in the corpus

• Natural Language Processing for EHR-Based Computational Phenotyping (2018, methodology): “[84] Manual, and MedLEE MedLEE map concepts to UMLS Discharge summaries, ICD-9 MedLEE concepts were manually reviewed by a clinician.”
• Bidirectional RNN for Medical Event Detection in Electronic Health Records (2016, background): “Haerian et al. (2012) applied distance supervision to identify terms (e.g., including “sui-cidal”, “self harm”, and “diphenhydramine over-dose”) associated with suicide events.”