Utilising Natural Language Processing to Identify Brain Tumor Patients for Clinical Trials: Development and Initial Evaluation Article Swipe

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James Booker , Jack Penn , Kawsar Noor , Richard Dobson , Naomi Fersht , Jonathan P. Funnell , Ciaran Scott Hill , Danyal Z. Khan , Nicola Newall , Thomas Searle , Siddharth Sinha , Lewis Thorne , Simon C. Williams , Michael Kosmin , Hani J. Marcus ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1016/j.wneu.2025.123907

NLP can be used effectively to extract brain tumor diagnoses from free-text EHR records with minimal additional training. The extracted concepts can then be linked to ongoing clinical trials. While further analysis is required to assess the impact on clinical outcomes, these findings suggest a potential application for integrating NLP algorithms into clinical care.

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Medicine Clinical trial Medical physics Natural language processing Pathology Computer science

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Type: article
Language: en
Landing Page: https://doi.org/10.1016/j.wneu.2025.123907
OA Status: hybrid
Cited By: 1
References: 21
Related Works: 10
OpenAlex ID: https://openalex.org/W4408568850

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OpenAlex ID: https://openalex.org/W4408568850

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DOI: https://doi.org/10.1016/j.wneu.2025.123907

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Title: Utilising Natural Language Processing to Identify Brain Tumor Patients for Clinical Trials: Development and Initial Evaluation

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Type: article

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Language: en

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Publication year: 2025

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Publication date: 2025-03-18

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Authors: James Booker, Jack Penn, Kawsar Noor, Richard Dobson, Naomi Fersht, Jonathan P. Funnell, Ciaran Scott Hill, Danyal Z. Khan, Nicola Newall, Thomas Searle, Siddharth Sinha, Lewis Thorne, Simon C. Williams, Michael Kosmin, Hani J. Marcus

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Landing page: https://doi.org/10.1016/j.wneu.2025.123907

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Open access: Yes

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OA status: hybrid

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OA URL: https://doi.org/10.1016/j.wneu.2025.123907

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Concepts: Medicine, Clinical trial, Medical physics, Natural language processing, Pathology, Computer science

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Cited by: 1

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Citations by year (recent): 2025: 1

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References (count): 21

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Related works (count): 10

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