Carr E, Bendayan R, Bean B, Stammers M, Wang W, Zhang H, Searle T, Kraljevic Z, Shek A, Phan HTT, Muruet W, Shinton AJ, Shi T, Zhang X, Pickles A, Stahl D, Zakeri R, O’Gallagher K, Folarin F, Roguski L, Borca F, Batchelor F, Wu X, Sun J, Pinto A, Guthrie B, Breen C, Douiri A, Wu H, Curcin V, Teo JT, Shah A, Dobson R (2020). “Supplementing the National Early Warning Score (NEWS2) for anticipating early deterioration among patients with COVID-19 infection”.medRxiv 2020.04.24.20078006. DOI: https://doi.org/10.1101/2020.04.24.20078006 (v3. 11 June 2020)
Bean D, Kraljevic Z, Searle T, Bendayan R, O’Gallagher K, Pickles A, Folarin A, Roguski L, Noor K, Shek A, Zakeri R, Shah A, Teo J, Dobson R (2020). “ACE-inhibitors and Angiotensin-2 Receptor Blockers are not associated with severe SARS- COVID19 infection in a multi-site UK acute Hospital Trust”. Accepted at the European Journal of Heart Failure. DOI: https://doi.org/10.1002/ejhf.1924 (2 June 2020)
Teo JT, Bean D, Bendeyan R, Dobson R, Shah A (2020). “Impact of ethnicity on outcome of severe COVID-19 infection. Data from an ethnically diverse UK tertiary centre”.medRxiv 2020.05.02.20078642. DOI: https://doi.org/10.1101/2020.05.02.20078642 (v4. 25 May 2020)
De Spiegeleer A, Bronselaer A, Teo JT, Byttebier G, De Tre G, Belmans L, Dobson R, Wynendaele E, Van De Wiele C, Vandaele F, Van Dijck D, Bean D, Fedson D, De Spiegeleer B (2020). “The effects of ARBs, ACEIs and statins on clinical outcomes of COVID-19 infection among nursing home residents”.medRxiv 2020.05.11.20096347. DOI: https://doi.org/10.1101/2020.05.11.20096347 (v1. 15 May 2020)
Ive J, Viani N, Kam J, Yin L, Verma S, Puntis S, Cardinal R, Roberts A, Stewart R, Velupillai S (2020). “Generation and evaluation of artificial mental health records for Natural Language Processing”.npj Digital Medicine 3, 69 (2020). DOI: https://doi.org/10.1038/s41746-020-0267-x (14 May 2020)
Song X, Downs J, Velupillai S, Holden R, Kikoler M, Bontcheva, K, Dutta R, Roberts A (2020). “Using Deep Neural Networks with Intra- and Inter-Sentence Context to Classify Suicidal Behaviour”.Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC 2020) , 1296–1303.https://www.aclweb.org/anthology/2020.lrec-1.163/ (11-16 May 2020)
Zhang H, Shi T, Wu X, Zhang X, Wang K, Bean D, Dobson R, Teo JT, Sun J, Zhao P, Li C, Dhaliwal K, Wu H, Li Q, Guthrie B (2020). “Risk prediction for poor outcome and death in hospital in-patients with COVID-19: derivation in Wuhan, China and external validation in London, UK”.medRxiv 2020.04.28.20082222. DOI: https://doi.org/10.1101/2020.04.28.20082222 (v1. 3 May 2020)
Sun S, Folarin A, Ranjan Y, Rashid Z, Conde P, Stewart C, Cummins N, Matcham F, Costa GD, Leocani L, Sørensen PS, Buron M, Guerrero AI, Zabalza A, Penninx BWJH, Lamers F, Siddi S, Haro JM, Myin-Germeys I, Rintala A, Narayan VA, Comi G, Hotopf M, Dobson RJB (on behalf of the RADAR-CNS consortium) (2020). “Using smartphones and wearable devices to monitor behavioural changes during COVID-19”. Under review at JMIR. arXiv:2004.14331.https://arxiv.org/abs/2004.14331 (v2. 1 May 2020)
Tissot H, Shah AD, Brealey D, Harris S, Agbakoba R, Folarin A, Romao L, Roguski L, Dobson R, Asselbergs FW (2020). “Natural Language Processing for Mimicking Clinical Trial Recruitment in Critical Care: A Semi-automated Simulation Based on the LeoPARDS Trial”.IEEE Journal of Biomedical and Health Informatics. DOI: https://doi.org/10.1109/JBHI.2020.2977925 (9 March 2020)
Kraljevic Z, Bean D, Mascio A, Roguski L, Folarin A, Roberts A, Bendayan R, Dobson R (2019). “MedCAT — Medical Concept Annotation Tool”.arXiv:1912.10166. https://arxiv.org/abs/1912.10166 (v1. 18 December 2019)
Bean DM, Teo J, Wu H, Oliveira R, Patel R, Bendayan, R, Shah AM, Dobson RJB, Scott PA (2019). “Semantic computational analysis of anticoagulation use in atrial fibrillation from real world data”.PLoS ONE 14(11): e0225625. DOI: https://doi.org/10.1371/journal.pone.0225625 (25 November 2019)
Searle T, Kraljevic Z, Bendayan R, Bean D, Dobson R (2019). “MedCATTrainer: A Biomedical Free Text Annotation Interface with Active Learning and Research Use Case Specific Customisation”.arXiv:1907.07322.https://arxiv.org/abs/1907.07322 (v1. 16 July 2019)
Wu H, Hodgson K, Dyson S, Morley KI, Ibrahim ZM, Iqbal E, Stewart R, Dobson RJB, Sudlow C (2019). “Efficient Reuse of Natural Language Processing Models for Phenotype-Mention Identification in Free-text Electronic Medical Records: A Phenotype Embedding Approach”.JMIR Med Inform 2019;7(4):e14782. DOI: https://doi.org/10.2196/14782 (22 May 2019)
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