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Dr. Ayoub Bagheri

Associate Professor 
Social and Behavioural Sciences
Social Sciences
Methodology and Statistics
Methodology and Statistics
Sjoerd Groenmangebouw
Padualaan 14
3584 CH Utrecht

Dr. Ayoub Bagheri

Associate Professor
Methodology and Statistics
a.bagheri@uu.nl
Profile Publications Activities Teaching Contact
Profile Publications Activities Teaching Contact
Areas of expertise
Skills
Research areas

Publications

2024

Scholarly publications

van Dalfsen, A., Karsdorp, F., Bagheri, A., Stronks, E., Mentink, D., & van Engelen, T. (2024). Direct and Indirect Annotation with Generative AI: A Case Study into Finding Animals and Plants in Historical Text. In Computational Humanities Research 2024: Proceedings of the Computational Humanities Research Conference 2024 Aarhus, Denmark, December 4-6, 2024. (pp. 1053-1074). CEUR WS. https://ceur-ws.org/Vol-3834/
https://research-portal.uu.nl/ws/files/246246290/paper74.pdf
Bron, M. P., Greijn, B., Coimbra, B. M., van de Schoot, R., & Bagheri, A. (2024). Combining Large Language Model Classifications and Active Learning for Improved Technology-Assisted Review. CEUR Workshop Proceedings, 3770, 77-95.
https://research-portal.uu.nl/ws/files/243875993/paper8.pdf
Mohammadi, H., Giachanou, A., & Bagheri, A. (2024). A Transparent Pipeline for Identifying Sexism in Social Media: Combining Explainability with Model Prediction. Applied Sciences (Switzerland), 14(19), Article 8620. https://doi.org/10.3390/app14198620
https://research-portal.uu.nl/ws/files/243695345/applsci-14-08620-v2.pdf
Fivez, P., Daelemans, W., Van de Cruys, T., Kashnitsky, Y., Chamezopoulos, S., Mohammadi, H., Giachanou, A., Bagheri, A., Poelman, W., Vladika, J., Ploeger, E., Bjerva, J., Matthes, F., & van Halteren, H. (2024). The CLIN33 Shared Task on the Detection of Text Generated by Large Language Models. Computational Linguistics in the Netherlands Journal, 13, 233-259. https://clinjournal.org/clinj/article/view/182
https://research-portal.uu.nl/ws/files/242911373/11_fivez_shared.pdf
Lim, Y. M. F., Asselbergs, F. W., Bagheri, A., Denaxas, S., Tay, W. T., Voors, A., Lam, C. S. P., Koudstaal, S., Grobbee, D. E., & Vaartjes, I. (2024). Eligibility of Asian and European registry patients for phase III trials in heart failure with reduced ejection fraction. ESC heart failure, 1-13. Advance online publication. https://doi.org/10.1002/ehf2.14751
Hedde-von Westernhagen, C., Bagheri, A., & Garcia-Bernardo, J. (2024). Predicting COVID-19 infections using multi-layer centrality measures in population-scale networks. Applied Network Science, 9(1), Article 27. https://doi.org/10.1007/s41109-024-00632-4
https://research-portal.uu.nl/ws/files/232283564/s41109-024-00632-4.pdf
Qi, Q., Bagheri, A., Hessen, D., & Van der Heijden, P. G. M. (2024). A comparison of correspondence analysis with PMI-based word embedding methods. arXiv. https://doi.org/10.48550/arXiv.2405.20895
https://dspace.library.uu.nl/bitstream/handle/1874/452787/2405.20895v1.pdf?sequence=1

2023

Scholarly publications

Mohammadi, H., Giachanou, A., & Bagheri, A. (2023). Towards Robust Online Sexism Detection: A Multi-Model Approach with BERT, XLM-RoBERTa, and DistilBERT for EXIST 2023 Tasks. In Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023) (pp. 1000-1011). Article 085 (CEUR Workshop Proceedings; Vol. 3497). CEUR WS. https://ceur-ws.org/Vol-3497/
https://dspace.library.uu.nl/bitstream/handle/1874/436560/paper-085.pdf?sequence=1
Teijema, J. J., Hofstee, L., Brouwer, M., de Bruin, J., Ferdinands, G., de Boer, J., Vizan, P., van den Brand, S., Bockting, C., van de Schoot, R., & Bagheri, A. (2023). Active learning-based systematic reviewing using switching classification models: the case of the onset, maintenance, and relapse of depressive disorders. Frontiers in Research Metrics and Analytics, 8, Article 1178181. https://doi.org/10.3389/frma.2023.1178181
https://dspace.library.uu.nl/bitstream/handle/1874/435312/frma-08-1178181.pdf?sequence=1
Fang, Q., Giachanou, A., Bagheri, A., Boeschoten, L., van Kesteren, E. J., Kamalabad, M. S., & Oberski, D. L. (2023). On Text-based Personality Computing: Challenges and Future Directions. In Findings of the Association for Computational Linguistics, ACL 2023 (pp. 10861-10879). (Proceedings of the Annual Meeting of the Association for Computational Linguistics). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-acl.691
https://dspace.library.uu.nl/bitstream/handle/1874/436397/2023.findings-acl.691.pdf?sequence=1
Bagheri, A., Giachanou, A., Mosteiro Romero, P., & Verberne, S. (2023). Natural Language Processing and Text Mining (Turning Unstructured Data into Structured). In F. Asselbergs, S. Denaxas, D. Oberski, & J. Moore (Eds.), Clinical Applications of Artificial Intelligence in Real-World Data (1 ed., pp. 69-93). Springer. https://doi.org/10.1007/978-3-031-36678-9_5
https://dspace.library.uu.nl/bitstream/handle/1874/436378/978-3-031-36678-9_5.pdf?sequence=1
Ferdinands, G., Schram, R., de Bruin, J., Bagheri, A., Oberski, D. L., Tummers, L., Teijema, J. J., & van de Schoot, R. (2023). Performance of active learning models for screening prioritization in systematic reviews: a simulation study into the Average Time to Discover relevant records. Systematic Reviews , 12(1), Article 100. https://doi.org/10.1186/s13643-023-02257-7
https://dspace.library.uu.nl/bitstream/handle/1874/434228/s13643-023-02257-7.pdf?sequence=1

Professional publications

van Leeuwen, A., Bagheri, A., Volker, T., & van Brakel, C. (2023). Verkenning van de inzet van topic modelling bij het analyseren van schrijfopdrachten. Tijdschrift voor Hoger Onderwijs, 41(2), 84-98. https://doi.org/10.59532/tvho.v41i2.15690
https://dspace.library.uu.nl/bitstream/handle/1874/433167/Verkenning_van_de_inzet_vantopic_modellingbij_het_analyseren_van_schrijfopdrachten.pdf?sequence=1

2022

Scholarly publications

Afsharizadeh, M., Ebrahimpour-Komleh, H., Bagheri, A., & Chrupala, G. (2022). A Survey on Multi-document Summarization and Domain-Oriented Approaches. Journal of Information Systems and Telecommunication, 10(37), 68-79. https://doi.org/10.52547/jist.16245.10.37.68
https://dspace.library.uu.nl/bitstream/handle/1874/425764/Article.pdf?sequence=1
de Jong, D., & Bagheri, A. (2022). The Case of Imperfect Negation Cues: A Two-Step Approach for Automatic Negation Scope Resolution. In P. Rosso, V. Basile, R. Martínez, E. Métais, & F. Meziane (Eds.), Natural Language Processing and Information Systems: 27th International Conference on Applications of Natural Language to Information Systems, NLDB 2022, Valencia, Spain, June 15–17, 2022, Proceedings (1 ed., pp. 413-424). (Lecture Notes in Computer Science; Vol. 13286 ). Springer. https://doi.org/10.1007/978-3-031-08473-7_38
https://dspace.library.uu.nl/bitstream/handle/1874/425955/978_3_031_08473_7_38.pdf?sequence=1
Teijema, J., Hofstee, L., Brouwer, M., Bruin, J. D., Ferdinands, G., Boer, J. D., Siso, P. V., Brand, S. A. G. E. V. D., Bockting, C., Schoot, R. V. D., & Bagheri, A. (2022). Active learning-based Systematic reviewing using switching classification models: the case of the onset, maintenance, and relapse of depressive disorders. PsyArXiv. https://doi.org/10.31234/osf.io/t7bpd
https://dspace.library.uu.nl/bitstream/handle/1874/437239/Mega-Meta_paper_1_-_Depression_Simulation_Paper_-_2202-07-15.pdf?sequence=1

2021

Scholarly publications

Yang, Z., Bagheri, A., & Van der Heijden, P. G. M. (2021). Neural Networks for Latent Budget Analysis of Compositional Data. (pp. 1-20). arXiv. https://doi.org/10.48550/arXiv.2109.04875
https://dspace.library.uu.nl/bitstream/handle/1874/416057/2109.04875v1.pdf?sequence=1
Felix, S. E. A., Bagheri, A., Ramjankhan, F. R., Spruit, M. R., Oberski, D., De Jonge, N., Van Laake, L. W., Suyker, W. J. L., & Asselbergs, F. W. (2021). A data mining-based cross-industry process for predicting major bleeding in mechanical circulatory support. European Heart Journal - Digital Health, 2(4), 635-642. https://doi.org/10.1093/ehjdh/ztab082
https://dspace.library.uu.nl/bitstream/handle/1874/415924/ztab082.pdf?sequence=1
Boverhof, B.-J., van de Schoot, R., & Bagheri, A. (2021). ASReview CNN HPO plugin. Software, Zenodo. https://doi.org/10.5281/zenodo.5482149
Teijema, J., de Bruin, J., van de Schoot, R., Hofstee, L., & Bagheri, A. (2021). ASReview wide doc2vec plugin. Software, Zenodo. https://doi.org/10.5281/zenodo.5084877
Vizán Siso, P., de Bruin, J., van de Schoot, R., Hofstee, L., & Bagheri, A. (2021). Code repository for: "Evaluation of the performance of neural network models and classical models in the context of Active Learning for Systematic Reviewing". Software https://doi.org/10.5281/ZENODO.5161100
Verberg, G., de Bruin, J., van de Schoot, R., Hofstee, L., & Bagheri, A. (2021). Scripts for a simulation on the effect of dataset size on neural network performance for active learning applied to systematic reviewing. Software, Zenodo. https://doi.org/10.5281/zenodo.5112498
Teijema, J., de Bruin, J., van de Schoot, R., Hofstee, L., & Bagheri, A. (2021). ASReview model switcher plugin. Software, Zenodo. https://doi.org/10.5281/zenodo.5084863
Bagheri, A., Groenhof, T. K. J., Asselbergs, F. W., Haitjema, S., Bots, M. L., Veldhuis, W. B., De Jong, P. A., & Oberski, D. L. (2021). Automatic Prediction of Recurrence of Major Cardiovascular Events: A Text Mining Study Using Chest X-Ray Reports. Journal of Healthcare Engineering, 2021, 1-11. Article 6663884. https://doi.org/10.1155/2021/6663884
https://dspace.library.uu.nl/bitstream/handle/1874/413665/6663884.pdf?sequence=1
Boeschoten, L., van Kesteren, E.-J., Bagheri, A., & Oberski, D. L. (2021). Achieving Fair Inference Using Error-Prone Outcomes. International Journal of Interactive Multimedia and Artificial Intelligence, 6(5), 9-15. https://doi.org/10.9781/ijimai.2021.02.007
https://dspace.library.uu.nl/bitstream/handle/1874/411989/ijimai_6_5_1_0.pdf?sequence=1
Sammani, A., Bagheri, A., van der Heijden, P. G. M., Te Riele, A. S. J. M., Baas, A. F., Oosters, C. A. J., Oberski, D., & Asselbergs, F. W. (2021). Automatic multilabel detection of ICD10 codes in Dutch cardiology discharge letters using neural networks. npj Digital Medicine, 4(1), 1-10. Article 37. https://doi.org/10.1038/s41746-021-00404-9
https://dspace.library.uu.nl/bitstream/handle/1874/411986/s41746_021_00404_9.pdf?sequence=1
Bagheri, A. (2021). Text Mining in Healthcare: Bringing Structure to Electronic Health Records. [Doctoral thesis 1 (Research UU / Graduation UU), Universiteit Utrecht]. Utrecht University. https://doi.org/10.33540/531
https://research-portal.uu.nl/ws/files/78041524/dissertation%20-%20ayoub%20bagheri%20-%205fe453c80af82.pdf

2020

Scholarly publications

Boeschoten, L., van Kesteren, E., Bagheri, A., & Oberski, D. L. (2020). Fair inference on error-prone outcomes. (pp. 1-14). arXiv. https://doi.org/10.48550/arXiv.2003.07621
https://dspace.library.uu.nl/bitstream/handle/1874/410479/2003.07621.pdf?sequence=1
Bagheri, A., Groenhof, T. K. J., Veldhuis, W. B., Jong, P. A. D., Asselbergs, F. W., & Oberski, D. L. (2020). Multimodal Learning for Cardiovascular Risk Prediction using EHR Data. (pp. 1-8). arXiv. https://doi.org/10.48550/arXiv.2008.11979
https://dspace.library.uu.nl/bitstream/handle/1874/419959/2008.11979v1.pdf?sequence=1
Afsharizadeh, M., Ebrahimpour-Komleh, H., & Bagheri, A. (2020). Automatic text summarization of COVID-19 research articles using recurrent neural networks and coreference resolution. Frontiers in Biomedical Technologies, 7(4), 236-248. https://doi.org/10.18502/fbt.v7i4.5321
https://research-portal.uu.nl/ws/files/234736285/5321-Article_Text-7482-1-10-20210407.pdf
Ferdinands, G., Schram, R., Bruin, J. D., Bagheri, A., Oberski, D. L., Tummers, L., & Schoot, R. V. D. (2020, Sept 16). Active learning for screening prioritization in systematic reviews - A simulation study. OSFPREPRINTS. https://doi.org/10.31219/osf.io/w6qbg
https://dspace.library.uu.nl/bitstream/handle/1874/415518/manuscript_Ferdinands.pdf?sequence=1
van de Leur, R. R., Boonstra, M. J., Bagheri, A., Roudijk, R. W., Sammani, A., Taha, K., Doevendans, P. A. F. M., van der Harst, P., van Dam, P. M., Hassink, R. J., van Es, R., & Asselbergs, F. W. (2020). Big data and artificial intelligence: Opportunities and threats in electrophysiology. Arrhythmia & Electrophysiology Review, 9(3), 146-154. https://doi.org/10.15420/aer.2020.26
https://dspace.library.uu.nl/bitstream/handle/1874/411063/aer_09_146.pdf?sequence=1
Bagheri, A., Sammani, A., van der Heijden, P. G. M., Asselbergs, F. W., & Oberski, D. L. (2020). ETM: Enrichment by topic modeling for automated clinical sentence classification to detect patients’ disease history. Journal of Intelligent Information Systems, 55(2), 329-349. https://doi.org/10.1007/s10844-020-00605-w
https://dspace.library.uu.nl/bitstream/handle/1874/409890/Bagheri2020_Article_ETMEnrichmentByTopicModelingFo.pdf?sequence=1
Bagheri, A., Sammani, A., van der Heijden, P. G. M., Asselbergs, F. W., & Oberski, D. L. (2020). Automatic ICD-10 Classification of Diseases from Dutch Discharge Letters. In In conjunction with the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSTEC 2020 https://www.insticc.org/node/TechnicalProgram/biostec/2020/presentationDetails/93726
https://dspace.library.uu.nl/bitstream/handle/1874/420196/Ayoub_ICDL1701.pdf?sequence=1
Bagheri, A., Sammani, A., Oberski, D. L., & Asselbergs, F. W. (2020). Multi-label ICD Classification of Dutch Hospital Discharge Letters. https://clin30.sites.uu.nl/accepted-submissions/

2019

Scholarly publications

Bagheri, A., Oberski, D. L., Sammani, A., van der Heijden, P. G. M., & Asselbergs, F. W. (2019). SALTClass: classifying clinical short notes using background knowledge from unlabeled data. https://doi.org/10.1101/801944
https://dspace.library.uu.nl/bitstream/handle/1874/390877/801944v1.full.pdf?sequence=1
Sedighi, Z., Ebrahimpour-Komleh, H., Bagheri, A., & Kosseim, L. (2019). Opinion Spam Detection with Attention-Based Neural Networks. In The Thirty-Second International Florida Artificial Intelligence Research Society Conference (FLAIRS-32) AAAI Press. https://aaai.org/ocs/index.php/FLAIRS/FLAIRS19/paper/view/18311
https://dspace.library.uu.nl/bitstream/handle/1874/394465/18311_78930_1_PB.pdf?sequence=1
Sammani, A., Jansen, M., Linschoten, M., Bagheri, A., & Asselbergs, F. W. (2019). UNRAVEL: big data analytics research data platform to improve care of patients with cardiomyopathies using routine electronic health records and standardised biobanking. Netherlands Heart Journal, 27, 426–434. https://doi.org/10.1007/s12471-019-1288-4
https://dspace.library.uu.nl/bitstream/handle/1874/390063/Sammani2019_Article_UNRAVELBigDataAnalyticsResearc.pdf?sequence=1
Bagheri, A. (2019). Integrating word status for joint detection of sentiment and aspect in reviews. Journal of Information Science, 45(6), 736-755. https://doi.org/10.1177/0165551518811458
https://dspace.library.uu.nl/bitstream/handle/1874/389765/0165551518811458.pdf?sequence=1

2018

Scholarly publications

Asgarnezhad, R., Monadjemi, S. A., Soltanaghaei, M., & Bagheri, A. (2018). SFT: A model for sentiment classification using supervised methods on twitter. Journal of Theoretical and Applied Information Technology, 96(8), 2242-2251.
Afsharizadeh, M., Ebrahimpour-Komleh, H., & Bagheri, A. (2018). Query-oriented text summarization using sentence extraction technique. In 2018 4th International Conference on Web Research, ICWR 2018 (pp. 128-132). (2018 4th International Conference on Web Research, ICWR 2018). IEEE. https://doi.org/10.1109/ICWR.2018.8387248
Sedighi, Z., Ebrahimpour-Komleh, H., & Bagheri, A. (2018). RLOSD: Representation learning based opinion spam detection. In Proceedings - 3rd Iranian Conference on Signal Processing and Intelligent Systems, ICSPIS 2017 (pp. 74-80). (Proceedings - 3rd Iranian Conference on Signal Processing and Intelligent Systems, ICSPIS 2017; Vol. 2017-December). IEEE. https://doi.org/10.1109/ICSPIS.2017.8311593

2016

Scholarly publications

Zaghian, A., & Bagheri, A. (2016). A combined model of clustering and classification methods for preserving privacy in social networks against inference and neighborhood attacks. International Journal of Security and its Applications, 10(1), 95-102. https://doi.org/10.14257/ijsia.2016.10.1.10

2014

Scholarly publications

Bagheri, A., & Saraee, M. (2014). Persian sentiment analyzer: A framework based on a novel feature selection method. International Journal of Artificial Intelligence, 12(2), 115-129.
Bagheri, A., Saraee, M., & De Jong, F. (2014). ADM-LDA: An aspect detection model based on topic modelling using the structure of review sentences. Journal of Information Science, 40(5), 621-636. https://doi.org/10.1177/0165551514538744

2013

Scholarly publications

Bagheri, A., Saraee, M., & de Jong, F. (2013). Latent Dirichlet Markov allocation for sentiment analysis. In In Proceeding of the Fifth European Conference on Intelligent Management Systems in Operations (pp. 90-96) https://ris.utwente.nl/ws/files/5511169/IMSIO_Latent_Dirichlet_Markov_Allocation.pdf
Bagheri, A., Saraee, M., & De Jong, F. (2013). Care more about customers: Unsupervised domain-independent aspect detection for sentiment analysis of customer reviews. Knowledge-Based Systems, 52, 201-213. https://doi.org/10.1016/j.knosys.2013.08.011
Bagheri, A., Saraee, M., & De Jong, F. (2013). An unsupervised aspect detection model for sentiment analysis of reviews. In Natural Language Processing and Information Systems - 18th International Conference on Applications of Natural Language to Information Systems, NLDB 2013, Proceedings (pp. 140-151). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7934 LNCS). https://doi.org/10.1007/978-3-642-38824-8_12
Saraee, M., & Bagheri, A. (2013). Feature selection methods in persian sentiment analysis. In Natural Language Processing and Information Systems - 18th International Conference on Applications of Natural Language to Information Systems, NLDB 2013, Proceedings (pp. 303-308). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7934 LNCS). https://doi.org/10.1007/978-3-642-38824-8_29
Bagheri, A., Saraee, M., & De Jong, F. (2013). Sentiment classification in Persian: Introducing a mutual information-based method for feature selection. In 2013 21st Iranian Conference on Electrical Engineering, ICEE 2013 Article 6599671 (2013 21st Iranian Conference on Electrical Engineering, ICEE 2013). https://doi.org/10.1109/IranianCEE.2013.6599671

2011

Scholarly publications

Moghimi, M., Saraee, M. H., & Bagheri, A. (2011). Modeling of batch annealing process using data mining techniques for cold rolled steel sheets. In 2011 IEEE International Conference on Mechatronics, ICM 2011 - Proceedings (pp. 277-281). Article 5971295 (2011 IEEE International Conference on Mechatronics, ICM 2011 - Proceedings). https://doi.org/10.1109/ICMECH.2011.5971295
Saraee, M., Moghimi, M., & Bagheri, A. (2011). Modeling batch annealing process using data mining techniques for cold rolled steel sheets. In Proceedings of the 1st International Workshop on Data Mining for Service and Maintenance, KDD4Service 2011 - Held in Conjunction with SIGKDD'11 (pp. 18-22). (Proceedings of the 1st International Workshop on Data Mining for Service and Maintenance, KDD4Service 2011 - Held in Conjunction with SIGKDD'11). https://doi.org/10.1145/2018673.2018677

2009

Scholarly publications

Norouzzadeh, M. S., Bagheri, A., & Saraee, M. H. (2009). Web search personalization: A fuzzy adaptive approach. In Proceedings - 2009 2nd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2009 (pp. 143-148). Article 5234590 (Proceedings - 2009 2nd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2009). https://doi.org/10.1109/ICCSIT.2009.5234590

2008

Scholarly publications

Bagheri, A., Akbarzadeh, M., & Saraee, M. (2008). Finding shortest path with learning algorithms. International Journal of Artificial Intelligence, 1. http://www.ceser.in/ceserp/index.php/ijai/article/view/779
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