ArticleJournal of patient experience2025
Natural Language Processing (NLP): Identifying Linguistic Gender Bias in Electronic Medical Records (EMRs).
Article in Journal of patient experience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Burden and risk factors of depression in seniors from 1990 to 2021: a multi-database study based on EMR mining methods.Translational psychiatry · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the rise of feminism, women report experiencing doubt or discrimination in medical settings. This study aims to explore the linguistic mechanisms by which physicians express disbelief toward patients and to investigate gender differences in the use of negative medical descriptions. A content analysis of 285 electronic medical records was conducted to identify 4 linguistic bias features: judging, reporting, quoting, and fudging. Sentiment classification and knowledge graph with ICD-11 were used to determine the prevalence of these features in the medical records, and logistic regression was applied to test gender differences. A total of 2354 descriptions were analyzed, with 64.7% of the patients identified as male. Descriptions of female patients contained fewer judgmental linguistic features but more fudging-related linguistic features compared to male patients (judging: OR 0.69, 95% CI 0.54-0.88,
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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 Socratic graph.