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B. Liu, J. Wang, K. Sun, G. Tsoumakas (2023), Fine-grained selective similarity integration for drug–target interaction prediction, Briefings in Bioinformatics
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Katsaki, S., Aivazidis, C., Mylonas, N., Mollas, I., Tsoumakas, G. (2023) On the Adaptability of Attention-Based Interpretability in Different Transformer Architectures for Multi-Class Classification Tasks, Proceedings of the AIMLAI Workshop of ECML PKDD 2023.
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Bardos, A., Mylonas, N., Mollas, I., Tsoumakas, G. (2023) Local interpretability of random forests for multi-target regression, Proceedings of the AIMLAI Workshop of ECML PKDD 2023.
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Mylonas, N., Mollas, I., Tsoumakas, G. An attention matrix for every decision: faithfulness-based arbitration among multiple attention-based interpretations of transformers in text classification. Data Min Knowl Disc, 38 (1), pp. 128 - 153, 2024.
D. Akrivousis, N. Mylonas, I. Mollas and G. Tsoumakas, "Text classification is keyphrase explainable! Exploring local interpretability of transformer models with keyphrase extraction," 2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA), Thessaloniki, Greece, 2023, pp. 1-9, doi: 10.1109/DSAA60987.2023.10302566.
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N. Mylonas, I. Mollas, B. Liu, Y. Manolopoulos and G. Tsoumakas, "On the Persistence of Multilabel Learning, Its Recent Trends, and Its Open Issues," in IEEE Intelligent Systems, vol. 38, no. 2, pp. 28-31, March-April 2023, doi: 10.1109/MIS.2023.3255591.
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Mylonas, N., Karlos, S., & Tsoumakas, G. (2023). WeakMeSH: Leveraging provenance information for weakly supervised classification of biomedical articles with emerging MeSH descriptors. Artificial Intelligence in Medicine, 137, 102505. doi:10.1016/j.artmed.2023.102505
N. Mylonas, I. Mollas and G. Tsoumakas, "Beyond Annual Revisions: A Multi-Label Concept Drift Analysis of MeSH", 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS), L'Aquila, Italy, 2023, pp. 157-162, doi: 10.1109/CBMS58004.2023.00209.
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Samaras, A., Bekiaridou, A., Papazoglou, A., Moysidis, D., Tsoumakas, G., Bamidis, P., Tsigkas, G, Lazaros, G., Kassimis, G., Fragakia, N., Vassilikos, V., Zarifis, I., Tziakas, D., Tsioufis, K., Davlouros, P., Giannakoulas, G. (2023) Artificial Intelligence-based Mining of Electronic Health Record Data to Accelerate the Digital Transformation of the National Cardiovascular Ecosystem: Design Protocol of the CardioMining study. BMJ Open.
Nikos Tsolakis, Christoniki Maga-Nteve, Georgios Meditskos, Stefanos Vrochidis, Ioannis Kompatsiaris, “Ince-PD model for Parkinson’s Disease Prediction using MDS-UPDRS I & II and PDQ-8 Score”, 19th International Conference on Artificial Intelligence Applications and Innovations (AIAI), 2023
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