This paper is in the following e-collection/theme issue:

Decision Support for Health Professionals (1127) ISRII-JMIR Mental and Behavioural Health journal (1) Electronic Health Records (961) Natural Language Processing (636) Articles* (13) Depression and Mood Disorders; Suicide Prevention (1271) Clinical Information and Decision Making (1314)

Published on in Vol 9, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22397, first published .
Using General-purpose Sentiment Lexicons for Suicide Risk Assessment in Electronic Health Records: Corpus-Based Analysis

Using General-purpose Sentiment Lexicons for Suicide Risk Assessment in Electronic Health Records: Corpus-Based Analysis

Using General-purpose Sentiment Lexicons for Suicide Risk Assessment in Electronic Health Records: Corpus-Based Analysis

Authors of this article:

André Bittar1 Author Orcid Image ;   Sumithra Velupillai1 Author Orcid Image ;   Angus Roberts1 Author Orcid Image ;   Rina Dutta1, 2 Author Orcid Image
Article Authors Cited by (8) Tweetations (4) Metrics

Journals

  1. Lagrari F, Elkettani Y. Traditional and Deep Learning Approaches for Sentiment Analysis: A Survey. Advances in Science, Technology and Engineering Systems Journal 2021;6(5):1 View
  2. Levis M, Levy J, Dufort V, Gobbel G, Watts B, Shiner B. Leveraging unstructured electronic medical record notes to derive population-specific suicide risk models. Psychiatry Research 2022;315:114703 View
  3. Denecke K, Reichenpfader D. Sentiment analysis of clinical narratives: A scoping review. Journal of Biomedical Informatics 2023;140:104336 View
  4. Yu H, Zuo X, Tang J, Fu Y. Identifying causal effects of the clinical sentiment of patients' nursing notes on anticipated fall risk stratification. Information Processing & Management 2023;60(6):103481 View
  5. Lu K, Meaney C, Guo E, Leung F. Evaluating the Applicability of Existing Lexicon-Based Sentiment Analysis Techniques on Family Medicine Resident Feedback Field Notes: Retrospective Cohort Study. JMIR Medical Education 2023;9:e41953 View
  6. Dutta R, Gkotsis G, Velupillai S, Downs J, Roberts A, Stewart R, Hotopf M. Identifying features of risk periods for suicide attempts using document frequency and language use in electronic health records. Frontiers in Psychiatry 2023;14 View
  7. Yao D, García de Soto B. Enhancing cyber risk identification in the construction industry using language models. Automation in Construction 2024;165:105565 View

Books/Policy Documents

  1. Mehta U, Bagali K, Kommanapalli S. AI, Consciousness and The New Humanism. View