ArticleEuropean journal of cardiovascular nursing2025
Exploring the full potential of the electronic health record: the application of natural language processing for clinical practice.
Article in European journal of cardiovascular nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- Systems Bioengineering of Septic Shock Metabolism: Citrulline, β-Hydroxybutyrate and Plasma Biomarker-Based Phenotyping.Biomolecules · 2026Review
- From evidence-based guidelines to practice: Using natural language processing to identify impactful interventions in falls prevention.International journal of nursing sciences · 2026Article
- Artificial intelligence in multidisciplinary tumor boards enhancing decision making and clinical outcomes in oncology.iScience · 2025Review
- Understanding Daily Care Experience Preferences Across the Lifespan of Older Adults: Application of Natural Language Processing.Western journal of nursing research · 2025Article
- Exploring Natural Language Processing through an Exemplar Using YouTube.International journal of environmental research and public health · 2024Article
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.
Funding
Abstract
The electronic health record (EHR) contains valuable patient data and offers opportunities to administer and analyse patients' individual needs longitudinally. However, most information in the EHR is currently stored in unstructured text notations. Natural language processing (NLP), a branch of artificial intelligence that enables computers to understand, interpret, and generate human language, can be used to delve into unstructured text data to uncover valuable insights and knowledge. This article discusses different types of NLP, the potential of NLP for cardiovascular nursing, and how to get started with NLP as a clinician.
Indexed as
Identifiers
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.