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Published in Proceedings of the Fifth Workshop on Scholarly Document Processing, Association for Computational Linguistics., 2025
A novel graph neural network that leverages both semantic and structural information to predict which research publications will lead to clinical trials. Our model analyses a comprehensive dataset of 19 million publication nodes, using transformer-based title and abstract sentence embeddings within their citation network context.
Recommended citation: Muller E, Boylan-Toomey J, Ekinsmyth J, Robben A, Cardona MDLP, Langfelder A. 2025. GraphTranslate: Predicting Clinical Trial Translation using Graph Neural Networks on Biomedical Literature. In Proceedings of the Fifth Workshop on Scholarly Document Processing (SDP 2025), pages 31–41, Vienna, Austria. Association for Computational Linguistics (ACL).
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Published in medRxiv., 2026
Chronic subdural hematoma (CSDH) is common and increasing in incidence. Short-term post-surgical outcomes are good, but longer term, patients experience increased morbidity and early mortality than controls and the general population. Deprivation and ethnicity affect many health conditions, but to our knowledge, this is the first UK study investigating their association with CSDH outcomes.
Recommended citation: Beyond the Haematoma: Socioeconomic Deprivation and Outcomes in Chronic Subdural Hematoma in a Single-Centre Cohort Study Emma Cook, Monica Fisk, Chloe Raggett, Kathryn Bush, Justin Boylan-Toomey, Michael G Hart medRxiv 2026.10.07.26364832; doi: https://doi.org/10.64898/2026.10.07.26364832
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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