Explanations of Machine Learning Models in Repeated Nested Cross-Validation: An Application in Age Prediction Using Brain Complexity Features

1 code implementation • Applied Sciences 2022 • Riccardo Scheda, Stefano Diciotti

In this work, we propose a general method to obtain representative SHAP values within a repeated nested cross-validation procedure and separately for the training and test sets of the different cross-validation rounds to assess the real generalization abilities of the explanations.

Effect of data leakage in brain MRI classification using 2D convolutional neural networks

1 code implementation • Scientific Reports 2021 • Ekin Yagis, Selamawet Workalemahu Atnafu, Alba García Seco De Herrera, Chiara Marzi, Riccardo Scheda, Marco Giannelli, Carlo Tessa, Luca Citi, Stefano Diciotti

In this study, we quantitatively assessed the effect of a data leakage caused by 3D MRI data splitting based on a 2D slice-level using three 2D CNN models to classify patients with Alzheimer’s disease (AD) and Parkinson’s disease (PD).

Deep Learning for Virus-Spreading Forecasting: a Brief Survey

no code implementations • 3 Mar 2021 • Federico Baldo, Lorenzo Dall'Olio, Mattia Ceccarelli, Riccardo Scheda, Michele Lombardi, Andrea Borghesi, Stefano Diciotti, Michela Milano

The advent of the coronavirus pandemic has sparked the interest in predictive models capable of forecasting virus-spreading, especially for boosting and supporting decision-making processes.

Decision Making