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Abdallah Alabdallah
Abdallah Alabdallah
Researcher, Center for Applied Intelligent Systems Research, Halmstad University
Zweryfikowany adres z hh.se
Tytuł
Cytowane przez
Cytowane przez
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The Concordance Index decomposition: A measure for a deeper understanding of survival prediction models
A Alabdallah, M Ohlsson, S Pashami, T Rögnvaldsson
Artificial Intelligence in Medicine 148, 102781, 2024
242024
Explainable predictive maintenance
S Pashami, S Nowaczyk, Y Fan, J Jakubowski, N Paiva, N Davari, ...
arXiv preprint arXiv:2306.05120, 2023
172023
SurvSHAP: a proxy-based algorithm for explaining survival models with SHAP
A Alabdallah, S Pashami, T Rögnvaldsson, M Ohlsson
2022 IEEE 9th international conference on data science and advanced …, 2022
112022
Discovering premature replacements in predictive maintenance time-to-event data
A Alabdallah, T Rognvaldsson, Y Fan, S Pashami, M Ohlsson
PHM Society Asia-Pacific Conference 4 (1), 2023
42023
Improving Concordance Index in Regression-based Survival Analysis: Evolutionary Discovery of Loss Function for Neural Networks
MG Altarabichi, A Alabdallah, S Pashami, T Rögnvaldsson, S Nowaczyk, ...
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2024
22024
Understanding survival models through counterfactual explanations
A Alabdallah, J Jakubowski, S Pashami, S Bobek, M Ohlsson, ...
International Conference on Computational Science, 310-324, 2024
22024
Heterogeneous Federated Learning via Personalized Generative Networks
Z Taghiyarrenani, A Alabdallah, S Nowaczyk, S Pashami
arXiv preprint arXiv:2308.13265, 2023
12023
Towards Trustworthy Survival Analysis with Machine Learning Models
A Alabdallah
Halmstad University Press, 2025
2025
CoxSE: Exploring the Potential of Self-Explaining Neural Networks with Cox Proportional Hazards Model for Survival Analysis
A Alabdallah, O Hamed, M Ohlsson, T Rögnvaldsson, S Pashami
arXiv preprint arXiv:2407.13849, 2024
2024
Machine Learning Survival Models: Performance and Explainability
A Alabdallah
Halmstad University Press, 2023
2023
Human Understandable Interpretation of Deep Neural Networks Decisions Using Generative Models
A Alabdallah
2019
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