Michela Carlotta Massi
PhD Student in Data Analytics and Decision Sciences






AFFILIATIONS

MOX Laboratory for Modeling and Scientific Computing

Department of Mathematics, Politecnico di Milano

Center for Health Data Science (CHDS)

Human Technopole

My research focuses on developing effective methodologies to represent highly complex genomic and medical data,

to enhance and complement interpretable and robust statistical approaches to classification, regression and survival modelling

to personalize treatment decisions within the precision medicine framework.

RECENT ARTICLES

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Franco N.R., Massi M.C., Ieva F. et al. (2021)

Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity

Radiotherapy and Oncology

Massi, M.C., Gasperoni, F., Ieva, F., Paganoni, A.m., Zunino, P., Manzoni, A., Franco, N.r., Et Al. (2020)

 

A deep learning approach validates genetic risk factors for late toxicity after prostate cancer radiotherapy in a REQUITE multinational cohort

 

Frontiers in Oncology

Massi, M.C., Ieva, F. (2021)

 

Learning Signal Representations for EEG Cross-subject Channel Selection and Trial Classification 

 

IEEE International Workshop on Machine Learning for Signal Processing

RELEVANT PREPRINTS

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Massi, M. C., Ieva, F., Gasperoni, F., & Paganoni, A. M. (2021).

 

Feature Selection for Imbalanced Data with Deep Sparse Autoencoders Ensemble

Manduchi, L., Marcinkeviks, R., Massi, M.C. (2021)

 

A Deep Variational Approach to Clustering Survival Data

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Massi, M. C., Franco, N.R., Ieva, F. et al (2021) 

 

Learning High-Order Interactions via Targeted Pattern Search