Ananiadou, S. - NaCTeM Publications - Aigaion 2.0

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Vorname(n):	S.
Nachname(n):	Ananiadou

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Li, M., Myrman, A. F., Mu, T. und Ananiadou, S., Modelling Instance-Level Annotator Reliability for Natural Language Labelling Tasks, in: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), Seiten 2873-2883, 2019

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Iliopoulos, I., Ananiadou, S., Danchin, A., Ioannidis, J. P. A., Katsikis, P. D., Ouzounis, C. A. und Promponas, V. J., Point of View: Hypothesis, analysis and synthesis, it's all Greek to me (2019), in: eLife, 8(e43514)

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Bannach-Brown, A., Przybyɫa, P., Thomas, J., Rice, A., Ananiadou, S., Liao, J. und Macleod, M. R., Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error (2019), in: Systematic Reviews, 8(23)

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Wang, Y., Ananiadou, S. und Tsujii, J., Improve Chinese Clinical Named Entity Recognition Performance by Using the Graphical and Phonetic Feature, in: Proceedings of the 2018 International Workshop on Biomedical and Health Informatics, 2018

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Nguyen, N. T. H., Gabud, R. und Ananiadou, S., COPIOUS: A gold standard corpus of named entities towards extracting species occurrence from biodiversity literature (2019), in: Biodiversity Data Journal, 7(e29626)

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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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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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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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