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All publications sorted by title
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| , , and , UK Institutional Repository Search: Innovation and Discovery (2009), in: Ariadne, 61 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and , UKPMC: a full text article resource for the life sciences (2010), in: Nucleic Acids Research, 39:Suppl. 1(D58-D65) |
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| and , Understanding Multimodal LLMs: the Mechanistic Interpretability of Llava in Visual Question Answering, arXiv, 2024 |
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| , , and , UoM&MMU at TSAR-2022 Shared Task: Prompt Learning for Lexical Simplification, in: Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022), pages 218-224, 2022 |
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| , , , , , and , User Engagement by User-Centred Design in e-Health (2010), in: Philosophical Transactions of the Royal Society A, 368:1926(4209-4224) |
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| , , and , Using a Random Forest Classifier to Compile Bilingual Dictionaries of Technical Terms from Comparable Corpora, in: Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers, Association for Computational Linguistics, Gothenburg, Sweden, pages 111-116, Association for Computational Linguistics, 2014 |
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| and , Using automatically learnt verb selectional preferences for classification of biomedical terms (2004), in: Journal of Biomedical Informatics, 37:6(483--497) |
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| , , and , Using Random Forest to recognise translation equivalents of biomedical terms across languages, in: Proceedings of the Sixth Workshop on Building and Using Comparable Corpora, Sofia, Bulgaria, pages 95-104, Association for Computational Linguistics, 2013 |
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| , , , and , Using text mining for study identification in systematic reviews: A systematic review of current approaches (2015), in: Systematic Reviews, 4:1 |
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| , , and , Using text mining techniques to extract phenotypic information from the PhenoCHF corpus (2015), in: BMC Medical Informatics and Decision Making, 15:Suppl. 2(S3) |
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| , , , , , , and , Using text mining to facilitate study identification in public health systematic reviews (2016), in: Guidelines International Network (G-I-N) conference |
| , , and , Using uncertainty to link and rank evidence from biomedical literature for model curation (2017), in: Bioinformatics |
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| , , , and , Using Workflows to Explore and Optimise Named Entity Recognition for Chemistry (2011), in: PLoS ONE, 6:5(e20181) |
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| and , What causes a causal relation? Detecting causal triggers in biomedical scientific discourse, in: 51st Annual Meeting of the Association for Computational Linguistics Proceedings of the Student Research Workshop, Sofia, Bulgaria, pages 38-45, Association for Computational Linguistics, 2013 |
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| and , What's in a Name? Entity Type Variation across Two Biomedical Subdomains, in: Proceedings of the Student Research Workshop at the 13th Conference of the European Chapter of the Association for Computational Linguistics, Avignon, France, pages 38-45, Association for Computational Linguistics, 2012 |
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| , , and , Why Biomedical Relation Extraction Results are Incomparable and What to do about it, in: Proceedings of the Third International Symposium on Semantic Mining in Biomedicine (SMBM 2008), pages 149--152, 2008 |
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| , , and , Wide coverage biomedical event extraction using multiple partially overlapping corpora (2013), in: BMC Bioinformatics, 14:175 |
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| , , , , and , Women’s health in The BMJ: a data science history (2020), in: BMJ Open, 10(e039759) |
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| , , , , , and , Youth Culturally adapted Manual Assisted Problem Solving Training (YCMAP) in Pakistani adolescent with a history of self harm: Protocol for multi-centre clinical and cost effectiveness randomised controlled trial (2022), in: BMJ Open, 12(e056301) |
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| , and , Zero-shot Temporal Relation Extraction with ChatGPT, in: Proceedings of BioNLP 2023, pages 92–102, 2023 |
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| 1-25 | 26-50 | 51-75 | 76-100 | 101-125 | 126-150 | 151-175 | 176-200 | 201-225 | 226-250 | 251-275 | 276-300 | 301-325 | 326-350 | 351-375 | 376-400 | 401-425 | 426-450 | 451-475 | 476-500 | 501-525 | 526-546 |