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Przybyɫa, P., Brockmeier, A. J. und Ananiadou, S., Quantifying Risk Factors in Medical Reports with a Context-Aware Linear Model (2019), in: Journal of the American Medical Informatics Association, 26:6(537â€“546)

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Shardlow, M., Ju., M., Li, M., O'Reilly, C., Iavarone, E., McNaught, J. und Ananiadou, S., A Text Mining Pipeline Using Active and Deep Learning for Curating Information in Computational Neuroscience (2018), in: Neuroinformatics

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Soto, A., Przybyɫa, P. und Ananiadou, S., Thalia: Semantic search engine for biomedical abstracts (2018), in: Bioinformatics, 35:10(1799â€“1801)

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Nghiem, M-. Q. und Ananiadou, S., APLenty: annotation tool for creating high-quality datasets using active and proactive learning, in: Proceedings of Empirical Methods in Natural Language Processing (System Demonstrations), 2018

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Thompson, P., Daikou, S., Ueno, K., Batista-Navarro, R., Tsujii, J. und Ananiadou, S., Annotation and Detection of Drug Effects in Text for Pharmacovigilance (2018), in: Journal of Cheminformatics, 10(37)

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Przybyɫa, P., Brockmeier, A. J., Kontonatsios, G., Le Pogam, M. -A., McNaught, J., von Elm, E., Nolan, K. und Ananiadou, S., Prioritising references for systematic reviews with RobotAnalyst: a user study (2018), in: Research Synthesis Methods, 9:3(470-488)

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Trieu, H-L., Nguyen, N. T. H., Miwa, M. und Ananiadou, S., Investigating Domain-Specific Information for Neural Coreference Resolution on Biomedical Texts, in: Proceedings of the BioNLP 2018 workshop, Seiten 183-188, 2018

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Raitano, G., Benfenati, E., Ananiadou, S., Nguyen, N. T. H., Do, Q. T., Rat, P. und Sousselier, L., Role of in silico tools and text mining in the safety assessment of selected plant coumarins (2017), in: Toxicology Letters, 280:Supplement 1(S96)

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Sousselier, L., Roncaglioni, A., Raitano, G., Petoumenou, M., Benfenati, E., Ananiadou, S., Nguyen, N. T. H., Do, Q. T., Paya, E., Olivier, E., Wakx, A., Michel, S., Dufat, H. und Rat, P., Role of in silico tools and text mining in the risk assessment of selected alkaloids (2018), in: Toxicology Letters, 295:Supplement 1(S159)

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Sousselier, L., Roncaglioni, A., Raitano, G., Petoumenou, M., Benfenati, E., Ananiadou, S., Nguyen, N. T. H., Do, Q. T., Olivier, E., Wakx, A. und Rat, P., Are all flavonoids safe for use in Cosmetics?, in: Proceedings of the 30th IFSCC Congress, Seiten Poster S2-296, 2018

Shardlow, M., Batista-Navarro, R., Thompson, P., Nawaz, R., McNaught, J. und Ananiadou, S., Identification of Research Hypotheses and New Knowledge from Scientific Literature (2018), in: BMC Medical Informatics and Decision Making, 18(46)

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Almagrabi, H., Malibari, A. und McNaught, J., Corpus Analysis and Annotation for Helpful Sentences in Product Reviews (2018), in: Computer and Information Science, 11:2(76-87)

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Christopoulou, F., Miwa, M. und Ananiadou, S., A Walk-based Model on Entity Graphs for Relation Extraction, in: Proceedings of ACL, Seiten 81-88, 2018

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Zerva, C. und Ananiadou, S., Paths for uncertainty: Exploring the intricacies of uncertainty identification for news, in: Proceedings of the NAACL Workshop on Computational Semantics Beyond Events and Roles (SemBEaR), Seiten 6-20, 2018

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Leroi, A. M., Lambert, B. C., Mauch, M., Papadopoulou, M., Ananiadou, S., Lindberg, S. I. I. und Lindenfors, P., On Revolutions (2018), in: V-Dem Working Paper(63)

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Yamada, T., Kamata, R., Ishinohachi, K., Shojima, N., Ananiadou, S., Noma, H., Yamauchi, T. und Kadowaki, T., Biosimilar Versus Originator Insulins: Systematic review and meta-analysis (2018), in: Diabetes, Obesity and Metabolism

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Arase, Y. und Tsujii, J., Monolingual Phrase Alignment on Parse Forests, in: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, Seiten 1-11, 2017

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Przybyɫa, P., Soto, A. und Ananiadou, S., Identifying Personalised Treatments and Clinical Trials for Precision Medicine using Semantic Search with Thalia, in: Proceedings of the Twenty-Fifth Text REtrieval Conference (TREC 2017), National Insitute of Standards and Technology, 2017

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Shardlow, M., Nguyen, N. T. H., Owen, G., Turner, S., O'Donovan, C., Leach, A., McNaught, J. und Ananiadou, S., A New Corpus to Support Text Mining for the Curation of Metabolites in the ChEBI Database, in: Proceedings of LREC 2018, Seiten 280-285, 2018

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Thompson, P. und Ananiadou, S., HYPHEN: A flexible, hybrid method to map phenotype concept mentions to terminological resources (2018), in: Terminology, 24:1(91-121)

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Ju., M., Miwa, M. und Ananiadou, S., A Neural Layered Model for Nested Named Entity Recognition, in: Proceedings of NAACL 2018, Seiten 1446-1459, 2018

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Brockmeier, A. J., Mu, T., Ananiadou, S. und Goulermas, J. Y, Self-Tuned Descriptive Document Clustering using a Predictive Network (2018), in: Transactions on Knowledge and Data Engineering

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Soto, A., Zerva, C., Batista-Navarro, R. und Ananiadou, S., LitPathExplorer: A Confidence-based Visual Text Analytics Tool for Exploring Literature-Enriched Pathway Models (2017), in: Bioinformatics, 34:8(1389-1397)

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Bahor, Z., Liao, J., Macleod, M. R., Bannach-Brown, A., McCann, S. K., Wever, K. E., Thomas, J., Ottavi, T., Howells, D. W., Rice, A., Ananiadou, S. und Sena, E., Risk of bias reporting in the recent animal focal cerebral ischaemia literature (2017), in: Clinical Science, 131:20(2525--2532)

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Li, M., Nguyen, N. T. H. und Ananiadou, S., Proactive Learning for Named Entity Recognition, in: Proceedings of BioNLP 2017, Seiten 117--125, Association for Computational Linguistics, 2017

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