Observational studyAMIA ... Annual Symposium proceedings. AMIA Symposium2019
Evaluating the Portability of an NLP System for Processing Echocardiograms: A Retrospective, Multi-site Observational Study.
Observational study in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis 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
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Systematic review of current natural language processing methods and applications in cardiology.Heart (British Cardiac Society) · 2022Pooled it
- Portability of a text mining algorithm for detecting adverse drug reactions in electronic health records across diverse patient groups in two Dutch hospitals.PLOS digital health · 2026Article
- Northwestern University resource and education development initiatives to advance collaborative artificial intelligence across the learning health system.Learning health systems · 2024Article
- A taxonomy for advancing systematic error analysis in multi-site electronic health record-based clinical concept extraction.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Rurality, Cardiovascular Risk Factors, and Early Cardiovascular Disease among Childhood, Adolescent, and Young Adult Cancer Survivors.Research square · 2024Article
- Artificial Intelligence in the Screening, Diagnosis, and Management of Aortic Stenosis.Reviews in cardiovascular medicine · 2024Review
- Informatics tools to implement late cardiovascular risk prediction modeling for population management of high-risk childhood cancer survivors.Pediatric blood & cancer · 2023Article
- Characterizing variability of electronic health record-driven phenotype definitions.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network.Scientific reports · 2023Article
- Comparison of State-of-the-Art Neural Network Survival Models with the Pooled Cohort Equations for Cardiovascular Disease Risk Prediction.BMC medical research methodology · 2023Article
- Prediction of left ventricular ejection fraction changes in heart failure patients using machine learning and electronic health records: a multi-site study.Scientific reports · 2023Article
- Automated interpretation of stress echocardiography reports using natural language processing.European heart journal. Digital health · 2022Article
- One Clinician Is All You Need-Cardiac Magnetic Resonance Imaging Measurement Extraction: Deep Learning Algorithm Development.JMIR medical informatics · 2022Article
- Integration and Validation of a Natural Language Processing Machine Learning Suicide Risk Prediction Model Based on Open-Ended Interview Language in the Emergency Department.Frontiers in digital health · 2022Article
- Leveraging Clinical Informatics Tools to Extract Cumulative Anthracycline Exposure, Measure Cardiovascular Outcomes, and Assess Guideline Adherence for Children With Cancer.JCO clinical cancer informatics · 2021Article
- Feasibility of capturing real-world data from health information technology systems at multiple centers to assess cardiac ablation device outcomes: A fit-for-purpose informatics analysis report.Journal of the American Medical Informatics Association : JAMIA · 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
17 authors at 3 institutions in 1 country.
Funding
Abstract
While natural language processing (NLP) of unstructured clinical narratives holds the potential for patient care and clinical research, portability of NLP approaches across multiple sites remains a major challenge. This study investigated the portability of an NLP system developed initially at the Department of Veterans Affairs (VA) to extract 27 key cardiac concepts from free-text or semi-structured echocardiograms from three academic edical centers: Weill Cornell Medicine, Mayo Clinic and Northwestern Medicine. While the NLP system showed high precision and recall easurements for four target concepts (aortic valve regurgitation, left atrium size at end systole, mitral valve regurgitation, tricuspid valve regurgitation) across all sites, we found moderate or poor results for the remaining concepts and the NLP system performance varied between individual sites.
Indexed as
Identifiers
32308812PMC7153064W2944017968What 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.