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Zhang, T., Yang, K, Alhuzali, H., Liu, B en Ananiadou, S., PHQ-aware depressive symptoms identification with similarity contrastive learning on social media (2023), in: Information Processing & Management, 60:5(103417)

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Vasquez-Rodriguez, L., Cuenca-Jimenez, P. -M., Morales-Esquivel, S. en Alva-Manchego, F., A Benchmark for Neural Readability Assessment of Texts in Spanish, in: Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022), pagina's 188–198, 2022

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Vasilakes, J., Georgiadis, P., Nguyen, N. T. H., Miwa, M. en Ananiadou, S., Contextualized Medication Event Extraction with Levitated Markers (2023), in: Journal of Biomedical Informatics(104347)

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Xie, Q., Huang, J., Saha, T en Ananiadou, S., GRETEL: Graph Contrastive Topic Enhanced Language Model for Long Document Extractive Summarization, in: Proceedings of COLING, pagina's 6259–6269, 2022

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Alhuzali, H., Zhang, T. en Ananiadou, S., Emotions and Topics Expressed on Twitter During the COVID-19 Pandemic in the United Kingdom: Comparative Geolocation and Text Mining Analysis (2022), in: Journal of Medical Internet Research, 24:10(e40323)

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Luo, Z., Xie, Q. en Ananiadou, S., Readability Controllable Biomedical Document Summarization, in: Findings of the Association for Computational Linguistics: EMNLP 2022, pagina's 4667–4680, 2022

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Cao, J., van Veen, E. M., Peek, N., Renehan, A. G en Ananiadou, S., A Novel Automated Approach to Mutation-Cancer Relation Extraction by Incorporating Heterogeneous Knowledge (2023), in: IEEE Journal of Biomedical and Health Informatics, 27:2(1096 - 1105)

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Schoene, A, Bojanic, L., Nghiem, M-. Q., Hunt, I. M. en Ananiadou, S., Classifying suicide-related content and emotions on Twitter using Graph Convolutional Neural Networks (2022), in: IEEE Transactions on Affective Computing(1-12)

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Vasquez-Rodriguez, L., Nguyen, N. T. H., Shardlow, M. en Ananiadou, S., 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), pagina's 218-224, 2022

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Luo, Z., Xie, Q. en Ananiadou, S., CitationSum: Citation-aware Graph Contrastive Learning for Scientific Paper Summarization, in: Proceedings of the ACM Web Conference, pagina's 1843–1852, 2023

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Nguyen, N. T. H., Miwa, M. en Ananiadou, S., Span-based Named Entity Recognition by Generating and Compressing Information, in: Proceedings of EACL 2023, pagina's 1984–1996, 2023

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Zhang, T., Yang, K, Shaoxiong, J. en Ananiadou, S., Emotion fusion for mental illness detection from social media: A survey (2023), in: Information Fusion, 92(231-246)

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Yang, K, Zhang, T., Alhuzali, H. en Ananiadou, S., Cluster-Level Contrastive Learning for Emotion Recognition in Conversations (2023), in: IEEE Transactions on Affective Computing(1-12)

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Alhuzali, H., Zhang, T. en Ananiadou, S., A comparative geolocation and text mining analysis of emotions and topics during the COVID-19 Pandemic in the UK (2022), in: Journal of Medical Internet Research

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Cao, J., van Veen, E. M., Peek, N., Renehan, A. G en Ananiadou, S., EPICURE: Ensemble Pretrained Models for Extracting Cancer Mutations from Literature, in: Proceedings of IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), pagina's 461-467, 2021

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Zhang, T., Schoene, A en Ananiadou, S., Automatic identification of suicide notes with a transformer-based deep learning model (2021), in: Internet Interventions(100422)

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Zerva, C., Taylor, S., Soto, A., Nguyen, N. T. H. en Ananiadou, S., A term-based and citation network-based search system for COVID-19 (2021), in: JAMIA Open, 4:4(ooab104)

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Wang, K., Stevens, R., Alachram, H., Li, Y., Soldatova, L. N., King, R. D., Ananiadou, S., Schoene, A, Li, M., Christopoulou, F., Ambite, J. L., Matthew, J., Garg, S., Hermjakob, U., Marcu, D., Sheng, E., Beissbarth, T., Wingender, E., Galstyan, A., Gao, X., Chambers, B., Pan, W., Khomtchouk, B. B., Evans, J. A. en Rzhetsky, A., NERO: a biomedical named-entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding (2021), in: npj systems biology and applications, 7(38)

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Navarro, T., Parrish, R., Cotoi, C., Germini, F., Linkins, L., Iorio, A., Haynes, R. B., Ananiadou, S. en Lokker, C., A Deep Learning Approach to Refine the Identification of High-Quality Clinical Research Articles From the Biomedical Literature: Protocol for Algorithm Development and Validation (2021), in: JMIR Research Protocols, 10:11(e29398)

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Trieu, H-L., Miwa, M. en Ananiadou, S., BioVAE: a pre-trained latent variable language model for biomedical text mining (2022), 38:3(872-874)

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Li, M. en Ananiadou, S., Neural Architectures for Aggregating Sequence Labels from Multiple Annotators (2022), in: Neurocomputing

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Xie, Q., Bishop, J., Tiwari, P. en Ananiadou, S., Pre-trained language models with domain knowledge for biomedical extractive summarization (2022), in: Knowledge-Based Systems, 252(109460)

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Espinosa, K., Georgiadis, P., Christopoulou, F., Ju., M., Miwa, M. en Ananiadou, S., Comparing neural models for nested and overlapping biomedical event detection (2022), in: BMC Bioinformatics, 23(211)

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Schoene, A, Basinas, I., van Tongeren, M. en Ananiadou, S., A Narrative Literature Review of Natural Language Processing Applied to the Occupational Exposome (2022), in: Int. J. Environ. Res. Public Health, 19:14(8544)

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Husain, N, Chaudhry, I. B., Taylor, P., Ananiadou, S., Aseem, S., Green, J. en Poppleton, A., 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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