Papapetrou, Panagiotis

Evaluating Local Interpretable Model-Agnostic Explanations on Clinical Machine Learning Classification Models

Barr Kumarakulasinghe, N., Blomberg, T., Liu, J., Saraiva Leao, A., & Papapetrou, P. (2020) · 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS)

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 133

Explainable AI for data-driven feedback and intelligent action recommendations to support students self-regulation

Afzaal, M., Nouri, J., Zia, A., Papapetrou, P., Fors, U., Wu, Y., Li, X., & Weegar, R. (2021) · Frontiers in Artificial Intelligence

Online Learning and AnalyticsIntelligent Tutoring Systems and Adaptive Learning

Cited by 125

A peek into the black box: exploring classifiers by randomization

Henelius, A., Puolamäki, K., Boström, H., Asker, L., & Papapetrou, P. (2014) · Data Mining and Knowledge Discovery

Explainable Artificial Intelligence (XAI)Data Mining Algorithms and Applications

Cited by 98

Explainable Time Series Tweaking via Irreversible and Reversible Temporal Transformations

Karlsson, I., Rebane, J., Papapetrou, P., & Gionis, A. (2018) · 2018 IEEE International Conference on Data Mining (ICDM)

Time Series Analysis and ForecastingExplainable Artificial Intelligence (XAI)

Cited by 31

CHiL(L)Grader: Calibrated Human-in-the-Loop Short-Answer Grading

Raikote, P., Randl, K., Miliou, I., Lakes, A., & Papapetrou, P. (2026) · arXiv

Educational Technology and AssessmentArtificial Intelligence in Education

Cited by 1