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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.
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Nentidis, A., Chatzopoulos, T., Krithara, A., et al. Large-scale investigation of weakly-supervised deep learning for the fine-grained semantic indexing of biomedical literature. Journal of Biomedical Informatics, Volume 146, 2023.
I. Mollas, N. Bassiliades, G. Tsoumakas, "Truthful meta-explanations for local interpretability of machine learning models", Applied Intelligence, 53, pp. 26927–26948, 2023.
Gaitanis, A.; Lentzas, A.; Tsoumakas, G.; Vrakas, D. Route Planning for Emergency Evacuation Using Graph Traversal Algorithms. Smart Cities 2023, 6, 1814-1831. https://doi.org/10.3390/smartcities6040084
Bin Liu, Dimitrios Papadopoulos, Fragkiskos D Malliaros, Grigorios Tsoumakas, Apostolos N Papadopoulos, Multiple similarity drug–target interaction prediction with random walks and matrix factorization, Briefings in Bioinformatics, Volume 23, Issue 5, September 2022, bbac353, https://doi.org/10.1093/bib/bbac353
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N. Mylonas, I. Mollas, N. Bassiliades, G. Tsoumakas, “Local Multi-Label Explanations for Random Forest”, 4th International Workshop on eXplainable Knowledge Discovery in Data Mining (XKDD 2022), 19 Sep 2022, Grenoble, France, In I. Koprinska et al. (Eds.): ECML PKDD 2022 Workshops, CCIS 1752, pp. 369–384, Springer Nature, 2023.
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Tatiana Passali, Thanassis Mavropoulos, Grigorios Tsoumakas, Georgios Meditskos and Stefanos Vrochidis. "LARD: Large-scale Artificial Disfluency Generation". In Proceedings of the Thirteenth Language Resources and Evaluation Conference, European Language Resources Association, 2022.
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E. Kouloumpris, A. Konstantinou, S. Karlos, G. Tsoumakas, and I. Vlahavas, “Short-term Load Forecasting With Clustered Hybrid Models Based On Hour Granularity”, In Proceedings of the 12th Hellenic Conference on Artificial Intelligence (SETN ’22), Corfu, Greece, 7-9 Sep 2022, Article 42, pp. 1–10, Association for Computing Machinery, 2022, DOI: https://doi.org/10.1145/3549737.3549783
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