Michela Massi

External Scientific collaborator

Contact Information

Phone:
+39 02 2399 4508
Fax:
+39 02 2399
Office:
14 nave
Email:

Keywords

Statistical learning
Health Analytics

Available MOX Reports

CAVINATO, L.; MASSI, M.C.; SOLLINI, M.; KIRIENKO , M.; IEVA, F.
Dual adversarial deconfounding autoencoder for joint batch-effects removal from multi-center and multi-scanner radiomics data
MASSI, M.C., DOMINONI, L., IEVA, F., FIORITO, G.
A Deep Survival EWAS approach estimating risk profile based on pre-diagnostic DNA methylation: an application to Breast Cancer time to diagnosis
MASSI, M.C.; IEVA, F.
Learning Signal Representations for EEG Cross-Subject Channel Selection and Trial Classification
MASSI, M.C.; GASPERONI, F.; IEVA, F.; PAGANONI, A.
Feature Selection for Imbalanced Data with Deep Sparse Autoencoders Ensemble
MASSI, M. C.; IEVA, F.
Representation Learning Methods for EEG Cross-Subject Channel Selection and Trial Classification
MASSI, M.C.; FRANCO, N.R; IEVA, F.; MANZONI, A.; PAGANONI, A.M.; ZUNINO, P.
High-Order Interaction Learning via Targeted Pattern Search
MASSI, M.C., GASPERONI, F., IEVA, F., PAGANONI, A.M., ZUNINO, P., MANZONI, A., FRANCO, N.R., ET AL.
A deep learning approach validates genetic risk factors for late toxicity after prostate cancer radiotherapy in a REQUITE multinational cohort
MASSI, M.C.; IEVA, F.; GASPERONI, F.; PAGANONI, A.M.
Minority Class Feature Selection through Semi-Supervised Deep Sparse Autoencoders
MASSI, M.C.; IEVA, F.; LETTIERI, E.
Data Mining Application to Healthcare Fraud Detection: A Two-Step Unsupervised Clustering Model for Outlier Detection with Administrative Databases
MASSIMI, PAOLO; QUARTERONI, ALFIO; SALERI, FAUSTO; SCROFANI, GIOVANNI
Modeling of Salt Tectonics
MASSIMI, PAOLO; QUARTERONI, ALFIO; SALERI, FAUSTO; SCROFANI, GIOVANNI
Modeling of Salt Tectonics
MASSIMI, PAOLO; QUARTERONI, ALFIO; SCROFANI, GIOVANNI
An adaptive finite element method for modeling salt diapirism
FORMAGGIA, LUCA; LAMPONI, DANIELE; TUVERI, MASSIMILIANO; VENEZIANI, ALESSANDRO
Numerical Modeling of 1D Arterial Networks Coupled with a Lumped Parameters Description of the Heart