Paola Stolfi

According to our database, Paola Stolfi authored at least 10 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

NIAPU: network-informed adaptive positive-unlabeled learning for disease gene identification.

Paola Stolfi, Andrea Mastropietro, Giuseppe Pasculli, Paolo Tieri, Davide Vergni

Bioinform., February, 2023

An agent-based multi-level model to study the spread of gonorrhea in different and interacting risk groups.

Paola Stolfi, Davide Vergni, Filippo Castiglione

Frontiers Appl. Math. Stat., 2023

2022

An agent-based multi-level model to study the spread of antimicrobial-resistant gonorrhoea.

Paola Stolfi, Davide Vergni, Rik Oldenkamp, Constance Schultsz, Emiliano Mancini, Filippo Castiglione

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

DruSiLa: an integrated, in-silico disease similarity-based approach for drug repurposing.

Pratuat Amatya, Paola Stolfi, Flavio Lombardi, Paolo Tieri

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021

Adaptive Positive-Unlabelled Learning via Markov Diffusion.

Paola Stolfi, Andrea Mastropietro, Giuseppe Pasculli, Paolo Tieri, Davide Vergni

CoRR, 2021

Emulating complex simulations by machine learning methods.

Paola Stolfi, Filippo Castiglione

BMC Bioinform., 2021

A functional data analysis approach to assess the prognostic value of SARS-CoV-2 infections surrogate data.

Paola Stolfi, Filippo Castiglione

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

A data-driven model for the generation of Virtual Cohorts.

Enrico Mastrostefano, Paola Stolfi, Filippo Castiglione

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

2020

Emulation of dynamic multi-output simulator of risk of type-2 diabetes.

Paola Stolfi, Filippo Castiglione

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2019

Potential predictors of type-2 diabetes risk: machine learning, synthetic data and wearable health devices.

Paola Stolfi, Ilaria Valentini, Maria Concetta Palumbo, Paolo Tieri, Andrea Grignolio, Filippo Castiglione

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019