ReviewJournal of biomedical informatics2015
Identifying risk factors for heart disease over time: Overview of 2014 i2b2/UTHealth shared task Track 2.
Review in Journal of biomedical informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
51 citing papers in PubMed, 3 syntheses or guidelines pooled it, 124 citations in OpenAlex.
- Use of unstructured text in prognostic clinical prediction models: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2022Pooled it
- Using Natural Language Processing to Measure and Improve Quality of Diabetes Care: A Systematic Review.Journal of diabetes science and technology · 2021Pooled it
- Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2019Pooled it
- Memorization in large language models in medicine prevalence characteristics and implications.Nature communications · 2026Article
- Leveraging free-text clinical records for heart disease classification through structured feature mapping.PloS one · 2026Article
- Cross- & multi-lingual medication detection: a transformer-based analysis.BMC medical informatics and decision making · 2025Article
- Large Language Model Symptom Identification From Clinical Text: Multicenter Study.Journal of medical Internet research · 2025Article
- A machine learning model using clinical notes to identify physician fatigue.Nature communications · 2025Article
- Combining unsupervised, supervised and rule-based learning: the case of detecting patient allergies in electronic health records.BMC medical informatics and decision making · 2023Article
- Overview of the 2022 n2c2 shared task on contextualized medication event extraction in clinical notes.Journal of biomedical informatics · 2023Review
- Heart disease risk factors detection from electronic health records using advanced NLP and deep learning techniques.Scientific reports · 2023Article
- Capturing Individual-level Social Determinants from Clinical Text.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- A scoping review of publicly available language tasks in clinical natural language processing.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Natural Language Processing: from Bedside to Everywhere.Yearbook of medical informatics · 2022Article
- SemClinBr - a multi-institutional and multi-specialty semantically annotated corpus for Portuguese clinical NLP tasks.Journal of biomedical semantics · 2022Article
- Prediction and risk stratification from hospital discharge records based on Hierarchical sLDA.BMC medical informatics and decision making · 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
- A Framework (SOCRATex) for Hierarchical Annotation of Unstructured Electronic Health Records and Integration Into a Standardized Medical Database: Development and Usability Study.JMIR medical informatics · 2021Article
- A comprehensive study of mobility functioning information in clinical notes: Entity hierarchy, corpus annotation, and sequence labeling.International journal of medical informatics · 2021Article
- Toward Understanding Clinical Context of Medication Change Events in Clinical Narratives.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
The second track of the 2014 i2b2/UTHealth natural language processing shared task focused on identifying medical risk factors related to Coronary Artery Disease (CAD) in the narratives of longitudinal medical records of diabetic patients. The risk factors included hypertension, hyperlipidemia, obesity, smoking status, and family history, as well as diabetes and CAD, and indicators that suggest the presence of those diseases. In addition to identifying the risk factors, this track of the 2014 i2b2/UTHealth shared task studied the presence and progression of the risk factors in longitudinal medical records. Twenty teams participated in this track, and submitted 49 system runs for evaluation. Six of the top 10 teams achieved F1 scores over 0.90, and all 10 scored over 0.87. The most successful system used a combination of additional annotations, external lexicons, hand-written rules and Support Vector Machines. The results of this track indicate that identification of risk factors and their progression over time is well within the reach of automated systems.
Indexed as
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What 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.