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Results: 24
Number of items: 24
  • Open Access
    Lin, B. Y., Mohammadi Ziabari, S. S., Nasser Al Husaini, Y., & Alsahag, A. M. M. (2026). SG-MuRCL: Smoothed Graph-Enhanced Multi-Instance Contrastive Learning for Robust Whole-Slide Image Classification. Information (Switzerland), 17(1), Article 37. https://doi.org/10.3390/info17010037
  • Open Access
    van Beveren, I., Sergidou, E., & Mohammadi Ziabari, S. (2026). Evaluating Deep Learning-Based Speaker Verification Systems: A Comparative Study Across Open-Source and Forensic Datasets. In A. Panchenko, D. Gubanov, M. Khachay, A. Kuznetsov, N. Loukachevitch, A. Kuznetsov, I. Nikishina, M. Panov, P. M. Pardalos, A. V. Savchenko, E. Tsymbalov, E. Tutubalina, A. Kasieva, & D. I. Ignatov (Eds.), Analysis of Images, Social Networks and Texts: 12th International Conference, AIST 2024, Bishkek, Kyrgyzstan, October 17–19, 2024 : revised selected papers (pp. 153-163). (Communications in Computer and Information Science; Vol. 2364). Springer. https://doi.org/10.1007/978-3-031-97019-1_12
  • Open Access
    Braakman, N. M., Mohammadi Ziabari, S. S., Alsahag, A. M. M., & Nasser Al Husaini, Y. (2026). Intrinsic interpretability at parity: Attention-Based RL–MIL for student outcome prediction. Natural Language Processing Journal, 14, Article 100204. https://doi.org/10.1016/j.nlp.2026.100204
  • Open Access
    Bakker, S., Ma, Y., & Mohammadi Ziabari, S. S. (2026). Addressing Label Scarcity: Hybrid Anomaly Detection in Mental Healthcare Billing. In E. Pardede, Q. Ma, G. Kotsis, T. Amagasa, A. Nadamoto, & I. Kahlil (Eds.), Information Integration and Web Intelligence: 27th International Conference, iiWAS 2025, Matsue, Japan, December 8–10, 2025 : proceedings (pp. 112–126). (Lecture Notes in Computer Science; Vol. 16330). Springer. https://doi.org/10.1007/978-3-032-11976-6_8
  • Open Access
    Leneman, T., Alsahag, A. M. M., & Mohammadi Ziabari, S. S. (2026). Explainable AI for subseasonal forecasting of the north atlantic oscillation. Machine Learning for Computational Science and Engineering, 2(1), Article 6. https://doi.org/10.1007/s44379-026-00055-1
  • Open Access
    Ahmadian, M., Bodalal, Z., Adib, M., Mohammadi Ziabari, S. S., Bos, P., Martens, R. M., Agrotis, G., Vens, C., Karssemakers, L., Al-Mamgani, A., de Graaf, P., Jasperse, B., Brakenhoff, R. H., Leemans, C. R., Beets-Tan, R. G. H., van den Brekel, M. W. M., & Castelijns, J. A. (2026). Explainable feature selection combining particle swarm optimisation with adaptive LASSO for MRI radiogenomics: Predicting HPV status in oropharyngeal cancer. Computer Methods and Programs in Biomedicine, 275, Article 109204. https://doi.org/10.1016/j.cmpb.2025.109204
  • Open Access
    Brakenhoff , B., Alsahag, A. M. M., & Mohammadi Ziabari, S. S. (2026). Dynamic GNNs for Predicting Train Cancellations on the Dutch Railway Network: A Multi-Season Study of Environmental and Operational Factors. Digital Technologies Research and Applications, 5(1), 32-52. https://doi.org/10.54963/dtra.v5i1.1709
  • Open Access
    Braakman, J., Mohammadi Ziabari, S. S., & Korver, A. (2025). Enhancing Soil Pollution Prediction Through Expert-Defined Risk Zones and Machine Learning: A Case Study in the Netherlands. In P. Delir Haghighi, M. Greguš, G. Kotsis, & I. Khalil (Eds.), Information Integration and Web Intelligence: 26th International Conference, iiWAS 2024, Bratislava, Slovak Republic, December 2–4, 2024 : proceedings (Vol. II, pp. 219-225). (Lecture Notes in Computer Science; Vol. 15343). Springer. https://doi.org/10.1007/978-3-031-78093-6_19
  • Open Access
    Tigchelaar, K., Mohammadi Ziabari, S. S., & Mulder, J. (2025). The Integration of Federated Learning Techniques in Predictive Aircraft Maintenance Using Cloud Services. In S. Wu, X. Su, X. Xu, & B. H. Kang (Eds.), Knowledge Management and Acquisition for Intelligent Systems: 20th Principle and Practice of Data and Knowledge Acquisition Workshop, PKAW 2024, Kyoto, Japan, November 18–19, 2024 : proceedings (pp. 203-213). (Lecture Notes in Computer Science; Vol. 15372), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-981-96-0026-7_16
  • Open Access
    Chen, J., Alsahag, A. M. M., & Mohammadi Ziabari, S. S. (2025). An analytics framework for interpretable subseasonal forecasting under decadal climate variability. Decision Analytics Journal, 17, Article 100660. https://doi.org/10.1016/j.dajour.2025.100660
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