ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2012
Methods for identifying suicide or suicidal ideation in EHRs.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
41 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations.International journal of environmental research and public health · 2020Pooled it
- Suicide Risk in 8- to 12-Year-Old Children: Retrospective Review of Emergency Department Electronic Health Records.JAACAP open · 2026Article
- Developing a Tool for Identifying Clinical Risk From Free-Text Clinical Records: Natural Language Processing Study.JMIR AI · 2025Article
- Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review.Drug safety · 2025Article
- Post-discharge suicide prediction among US veterans using natural language processing-enriched social and behavioral determinants of health.Npj mental health research · 2025Article
- Predicting Suicide Among US Veterans Using Natural Language Processing-enriched Social and Behavioral Determinants of Health.Research square · 2024Article
- Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review.JMIR medical informatics · 2023Review
- A multisite comparison using electronic health records and natural language processing to identify the association between suicidality and hospital readmission amongst patients with eating disorders.The International journal of eating disorders · 2023Article
- Identifying features of risk periods for suicide attempts using document frequency and language use in electronic health records.Frontiers in psychiatry · 2023Article
- Detection of Suicidal Behavior and Self-harm Among Children Presenting to Emergency Departments: A Tree-based Classification Approach.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
- Portability of natural language processing methods to detect suicidality from clinical text in US and UK electronic health records.Journal of affective disorders reports · 2022Article
- Improving ascertainment of suicidal ideation and suicide attempt with natural language processing.Scientific reports · 2022Article
- ScAN: Suicide Attempt and Ideation Events Dataset.Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting · 2022Article
- Suicidal Ideation and Suicide-Attempt-Related Hospitalizations among People with Alzheimer's Disease (AD) and AD-Related Dementias in the United States during 2016-2018.Journal of clinical medicine · 2022Article
- Article
- Analysis of Suicide Methods and Substances Influencing the State of Consciousness of Their Victims in Poland.International journal of environmental research and public health · 2021Article
- Using weak supervision and deep learning to classify clinical notes for identification of current suicidal ideation.Journal of psychiatric research · 2021Article
- Developing a Natural Language Processing tool to identify perinatal self-harm in electronic healthcare records.PloS one · 2021Article
- Identifying and Predicting Intentional Self-Harm in Electronic Health Record Clinical Notes: Deep Learning Approach.JMIR medical informatics · 2020Article
- Validation of an alcohol misuse classifier in hospitalized patients.Alcohol (Fayetteville, N.Y.) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Electronic health records contain important data elements for detection of novel adverse drug reactions, genotype/phenotype identification and psychosocial factor analysis, and the role of each of these as risk factors for suicidality warrants further investigation. Suicide and suicidal ideation are documented in clinical narratives. The specific purpose of this study was to define an algorithm for automated detection of this serious event. We found that ICD-9 E-Codes had the lowest positive predictive value: 0.55 (90% CI: 0.42-0.67), while combining ICD-9 and NLP had the best PPV: 0.97 (90% CI: 0.92-0.99). A qualitative analysis and classification of the types of errors by ICD-9 and NLP automated coding compared to manual review are also discussed.
Indexed as
Identifiers
23304402PMC3540459What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.