14 citations · 22 across the 10 of their papers we have counts for
12 papers
Hierarchical Attention Network for Interpretable ECG-based Heart Disease Classification
Mario Padilla Rodriguez, Mohamed Nafea
Cardiovascular disease remains one of the leading causes of mortality worldwide, underscoring the need for accurate as well as interpretable diagnostic machine learning tools. In t…
Centralized and Federated Heart Disease Classification Models Using UCI Dataset and their Shapley-value Based Interpretability
Mario Padilla Rodriguez, Mohamed Nafea
Cardiovascular diseases are a leading cause of mortality worldwide, highlighting the need for accurate diagnostic methods. This study benchmarks centralized and federated machine l…
Causal Discovery in Linear Models with Unobserved Variables and Measurement Error
Yuqin Yang, Mohamed Nafea, Negar Kiyavash +2
The presence of unobserved common causes and measurement error poses two major obstacles to causal structure learning, since ignoring either source of complexity can induce spuriou…
Causal Discovery in Linear Latent Variable Models Subject to Measurement Error
Yuqin Yang, AmirEmad Ghassami, Mohamed Nafea +3
We focus on causal discovery in the presence of measurement error in linear systems where the mixing matrix, i.e., the matrix indicating the independent exogenous noise terms perta…
Causal Discovery in Linear Structural Causal Models with Deterministic Relations
Yuqin Yang, Mohamed Nafea, AmirEmad Ghassami +1
Linear structural causal models (SCMs) -- in which each observed variable is generated by a subset of the other observed variables as well as a subset of the exogenous sources -- a…
Information Theoretic Measures for Fairness-aware Feature Selection
Sajad Khodadadian, Mohamed Nafea, AmirEmad Ghassami +1
Machine learning algorithms are increasingly used for consequential decision making regarding individuals based on their relevant features. Features that are relevant for accurate…