Ananiadou, S. - NaCTeM Publications - Aigaion 2.0

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Primeiro nome(s):	S.
Sobrenome(s):	Ananiadou

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Lambert, B. C., Kontonatsios, G., Mauch, M., Kokkoris, T., Jockers, M., Ananiadou, S. and Leroi, A. M., The pace of modern culture (2020), in: Nature Human Behaviour

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Hamulyak, E. N., Brockmeier, A. J., Killas, J. D., Ananiadou, S., Middeldorp, S. and Leroi, A. M., Women’s health in The BMJ: a data science history (2020), in: BMJ Open, 10(e039759)

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Espinosa, K., Miwa, M. and Ananiadou, S., A Search-based Neural Model for Biomedical Nested and Overlapping Event Detection, in: Proceedings of EMNLP 2019, páginas 3670-3677, 2019

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Christopoulou, F., Tran, T. T., Sahu, S. K., Miwa, M. and Ananiadou, S., Adverse Drug Events and Medication Relation Extraction in EHRs with Ensemble Deep Learning Methods (2019), in: Journal of the American Medical Informatics Association(ocz101)

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Ju., M., Nguyen, N. T. H., Miwa, M. and Ananiadou, S., An Ensemble of Neural Models for Nested Adverse Drug Events and Medication Extraction with Subwords (2019), in: Journal of the American Medical Informatics Association, 27:1(22-30)

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Ju., M., Short, A.D., Thompson, P., Bakerly, N. D., Gkoutos, G., Tsaprouni, L. and Ananiadou, S., Annotating and Detecting Phenotypic Information for Chronic Obstructive Pulmonary Disease (2019), in: JAMIA Open, 2:2(261-271)

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Christopoulou, F., Miwa, M. and Ananiadou, S., Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs, in: Proceedings of EMNLP 2019, páginas 4927-4938, 2019

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Nguyen, N. T. H., Gabud, R. and 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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Trieu, H-L., Duong, K. N. A., Nguyen, N. T. H., Miwa, M., Takamura, H. and Ananiadou, S., Coreference Resolution in Full Text Articles with BERT and Syntax-based Mention Filtering, in: Proceedings of the 5th Workshop on BioNLP Open Shared Tasks, páginas 196-205, 2019

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Alhuzali, H. and Ananiadou, S., Improving classification of Adverse Drug Reactions through Using Sentiment Analysis and Transfer Learning, in: Proceedings of BioNLP, páginas 339-347, 2019

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Brockmeier, A. J., Ju., M., Przybyɫa, P. and Ananiadou, S., Improving reference prioritisation with PICO recognition (2019), in: BMC Medical Informatics and Decision Making, 19(256)

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Sahu, S. K., Christopoulou, F., Miwa, M. and Ananiadou, S., Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network, in: Proceedings of ACL 2019, páginas 4309-4316, 2019

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Bannach-Brown, A., Przybyɫa, P., Thomas, J., Rice, A., Ananiadou, S., Liao, J. and 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., Fan, X., Chen, L., Chang, E. I-C., Ananiadou, S., Tsujii, J. and Xu, Y., Mapping anatomical related entities to human body parts based on wikipedia in discharge summaries (2019), in: BMC Bioinformatics, 20(430)

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Li, M., Myrman, A. F., Mu, T. and 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), páginas 2873-2883, 2019

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Iliopoulos, I., Ananiadou, S., Danchin, A., Ioannidis, J. P. A., Katsikis, P. D., Ouzounis, C. A. and 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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Przybyɫa, P., Brockmeier, A. J. and 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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Ju., M., Miwa, M. and Ananiadou, S., A Neural Layered Model for Nested Named Entity Recognition, in: Proceedings of NAACL 2018, páginas 1446-1459, 2018

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

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

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

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

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

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

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