ArticleJournal of biomedical informatics2013
Annotating temporal information in clinical narratives.
Article in Journal of biomedical informatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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
31 citing papers in PubMed.
- Leveraging Generative Large Language Models for Temporal Relation Extraction From French Clinical Narratives: Prompt-Chaining Approach.Journal of medical Internet research · 2026Article
- Temporal Annotation of German Clinical Language in Real and Synthetic Clinical Documents: Corpus Development and Baseline Tagger Validation Study.Journal of medical Internet research · 2026Article
- End-to-end extraction of temporal information from psychiatric discharge summaries.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026Article
- Transformers and large language models in healthcare: A review.Artificial intelligence in medicine · 2024Review
- Multimodal learning for temporal relation extraction in clinical texts.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Using Multimodal Data to Improve Precision of Inpatient Event Timelines.Advances in knowledge discovery and data mining : ... Pacific-Asia Conference, PAKDD ..., proceedings. Pacific-Asia Conference on Knowledge Discovery and Data Mining · 2024Article
- Typed Markers and Context for Clinical Temporal Relation Extraction.Proceedings of machine learning research · 2023Article
- End-to-end clinical temporal information extraction with multi-head attention.Proceedings of the conference. Association for Computational Linguistics. Meeting · 2023Article
- Heart disease risk factors detection from electronic health records using advanced NLP and deep learning techniques.Scientific reports · 2023Article
- Parameter Efficient Transfer Learning for Suicide Attempt and Ideation Detection.Proceedings of the ... International Workshop on Health Text Mining and Information Analysis · 2022Article
- Predicting Age-related Macular Degeneration Progression with Longitudinal Fundus Images Using Deep Learning.Machine learning in medical imaging. MLMI (Workshop) · 2022Article
- SemClinBr - a multi-institutional and multi-specialty semantically annotated corpus for Portuguese clinical NLP tasks.Journal of biomedical semantics · 2022Article
- A Review of Recent Work in Transfer Learning and Domain Adaptation for Natural Language Processing of Electronic Health Records.Yearbook of medical informatics · 2021Review
- Time event ontology (TEO): to support semantic representation and reasoning of complex temporal relations of clinical events.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Temporal information extraction from mental health records to identify duration of untreated psychosis.Journal of biomedical semantics · 2020Article
- Extraction and Analysis of Clinically Important Follow-up Recommendations in a Large Radiology Dataset.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020Article
- Extraction of Temporal Information from Clinical Narratives.Journal of healthcare informatics research · 2019Article
- A general approach for improving deep learning-based medical relation extraction using a pre-trained model and fine-tuning.Database : the journal of biological databases and curation · 2019Article
- Identifying direct temporal relations between time and events from clinical notes.BMC medical informatics and decision making · 2018Article
- Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources.JMIR medical informatics · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Temporal information in clinical narratives plays an important role in patients' diagnosis, treatment and prognosis. In order to represent narrative information accurately, medical natural language processing (MLP) systems need to correctly identify and interpret temporal information. To promote research in this area, the Informatics for Integrating Biology and the Bedside (i2b2) project developed a temporally annotated corpus of clinical narratives. This corpus contains 310 de-identified discharge summaries, with annotations of clinical events, temporal expressions and temporal relations. This paper describes the process followed for the development of this corpus and discusses annotation guideline development, annotation methodology, and corpus quality.
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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.