16 citations · 40 across the 35 of their papers we have counts for
5 papers · 1 filter
A general framework for penalized mixed-effects multitask learning with applications on DNA methylation surrogate biomarkers creation
Andrea Cappozzo, Francesca Ieva, Giovanni Fiorito
Recent evidence highlights the usefulness of DNA methylation (DNAm) biomarkers as surrogates for exposure to risk factors for non-communicable diseases in epidemiological studies a…
Longitudinal Latent Overall Toxicity (LOTox) profiles in osteosarcoma: a new taxonomy based on latent Markov models
Marta Spreafico, Francesca Ieva, Marta Fiocco
Due to the presence of multiple types of adverse events with different levels of severity, the analysis of longitudinal toxicity data is a difficult task in cancer studies. In this…
Learning Signal Representations for EEG Cross-Subject Channel Selection and Trial Classification
Michela C. Massi, Francesca Ieva
EEG technology finds applications in several domains. Currently, most EEG systems require subjects to wear several electrodes on the scalp to be effective. However, several channel…
Feature Selection for Imbalanced Data with Deep Sparse Autoencoders Ensemble
Michela C. Massi, Francesca Ieva, Francesca Gasperoni +1
Class imbalance is a common issue in many domain applications of learning algorithms. Oftentimes, in the same domains it is much more relevant to correctly classify and profile min…
Learning High-Order Interactions via Targeted Pattern Search
Michela C. Massi, Nicola R. Franco, Francesca Ieva +3
Logistic Regression (LR) is a widely used statistical method in empirical binary classification studies. However, real-life scenarios oftentimes share complexities that prevent fro…