ArticleJournal of medical Internet research2021
Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record's Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study.
Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.
What it found
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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
23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 38 citations in OpenAlex.
- AI Quality Standards in Health Care: Rapid Umbrella Review.Journal of medical Internet research · 2024Pooled it
- Improving Clinical Documentation with Artificial Intelligence: A Systematic Review.Perspectives in health information management · 2024Pooled it
- Systematic Review of Large Language Models and Natural Language Processing in Stroke Care: Applications, Challenges, and Future Directions.Stroke (Hoboken, N.J.) · 2026Review
- Effect of internet plus nursing mode telehealth intervention on warfarin management in atrial fibrillation patients.Frontiers in cardiovascular medicine · 2026Article
- Are Machine Learning methods effective in detecting undiagnosed atrial fibrillation in primary care settings using electronic health records? A systematic review.PLOS digital health · 2025Article
- Reframing EHR Policy in China: Towards Balanced Implementation and Ethical Foundations.Journal of evaluation in clinical practice · 2025Article
- Evaluation of Care Quality for Atrial Fibrillation Across Non-Interoperable Electronic Health Record Data using a Retrieval-Augmented Generation-enabled Large Language Model.medRxiv : the preprint server for health sciences · 2025Article
- Semantic Relations: Extending SNOMED CT and Solor.Applied clinical informatics · 2025Article
- Trends in electronic health record metadata use for management purposes.Learning health systems · 2025Article
- Improving Phenotyping of Patients With Immune-Mediated Inflammatory Diseases Through Automated Processing of Discharge Summaries: Multicenter Cohort Study.JMIR medical informatics · 2025Article
- Semantic Clinical Artificial Intelligence vs Native Large Language Model Performance on the USMLE.JAMA network open · 2025Article
- Stroke Diagnosis and Prediction Tool Using ChatGLM: Development and Validation Study.Journal of medical Internet research · 2025Article
- Data science and artificial intelligence in biology, health, and healthcare.Journal of clinical and translational science · 2025Article
- The Sociodemographic Biases in Machine Learning Algorithms: A Biomedical Informatics Perspective.Life (Basel, Switzerland) · 2024Article
- [Artificial intelligence in wearable electrocardiogram monitoring].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023Article
- Applications of the Natural Language Processing Tool ChatGPT in Clinical Practice: Comparative Study and Augmented Systematic Review.JMIR medical informatics · 2023Article
- Applications of Natural Language Processing for the Management of Stroke Disorders: Scoping Review.JMIR medical informatics · 2023Article
- Doctors Identify Hemorrhage Better during Chart Review when Assisted by Artificial Intelligence.Applied clinical informatics · 2023Article
- Effectiveness of Using the FreeStyle LibreDiagnostics (Basel, Switzerland) · 2023Review
- The Real-World Experiences of Persons With Multiple Sclerosis During the First COVID-19 Lockdown: Application of Natural Language Processing.JMIR medical informatics · 2022Article
Corrections and comments
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Authors and funding
16 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundNonvalvular atrial fibrillation (NVAF) affects almost 6 million Americans and is a major contributor to stroke but is significantly undiagnosed and undertreated despite explicit guidelines for oral anticoagulation.
objectiveThe aim of this study is to investigate whether the use of semisupervised natural language processing (NLP) of electronic health record's (EHR) free-text information combined with structured EHR data improves NVAF discovery and treatment and perhaps offers a method to prevent thousands of deaths and save billions of dollars.
methodsWe abstracted 96,681 participants from the University of Buffalo faculty practice's EHR. NLP was used to index the notes and compare the ability to identify NVAF, congestive heart failure, hypertension, age ≥75 years, diabetes mellitus, stroke or transient ischemic attack, vascular disease, age 65 to 74 years, sex category (CHA
resultsThe structured-plus-unstructured method would have identified 3,976,056 additional true NVAF cases (P<.001) and improved sensitivity for CHA
conclusionsArtificial intelligence-informed bio-surveillance combining NLP of free-text information with structured EHR data improves data completeness, prevents thousands of strokes, and saves lives and funds. This method is applicable to many disorders with profound public health consequences.
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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.