Irene POLI

Position
Senior Researcher
E-mail
irenpoli@unive.it
Scientific sector (SSD)
STATISTICA [SECS-S/01]
Website
www.unive.it/people/irenpoli (personal record)
Office
European Center for Living Technology (ECLT)
Where: Ca' Bottacin
Office
Department of Environmental Sciences, Informatics and Statistics
Website: https://www.unive.it/dep.dais
Where: Campus scientifico via Torino
Research Institute
Research Institute for Complexity

Abebe, Seyum; Poli, Irene; Jones, Roger D.; Slanzi, Debora Learning Optimal Dynamic Treatment Regime from Observational Clinical Data through Reinforcement Learning in MACHINE LEARNING AND KNOWLEDGE EXTRACTION, vol. 6, pp. 1798-1817 (ISSN 2504-4990)
DOI 2024, Articolo su rivista - Scheda ARCA: 10278/5069103


Slanzi, Debora; Silvestri, Claudio; Poli, Irene; Mayer, Gert Exploiting the Potential of Bayesian Networks in Deriving New Insight into Diabetic Kidney Disease (DKD) in Villani, M., Cagnoni, S., Serra, R., Artificial Life and Evolutionary Computation. WIVACE 2023., Springer, vol. 1977, pp. 298-308 (ISBN 9783031574290; 9783031574306) (ISSN 1865-0929)
DOI 2024, Articolo su libro - Scheda ARCA: 10278/5054921


Jones, Roger D; Abebe, Seyum; Distefano, Veronica; Mayer, Gert; Poli, Irene; Silvestri, Claudio; Slanzi, Debora Candidate composite biomarker to inform drug treatments for diabetic kidney disease in FRONTIERS IN MEDICINE, vol. 10, pp. 1271407 (ISSN 2296-858X)
DOI 2023, Articolo su rivista - Scheda ARCA: 10278/5044320


Mameli, Valentina; Slanzi, Debora; Poli, Irene; Green, Darren V S Search for relevant subsets of binary predictors in high dimensional regression for discovering the lead molecule in PHARMACEUTICAL STATISTICS, vol. 20, pp. 898-915 (ISSN 1539-1604)
DOI 2021, Articolo su rivista - Scheda ARCA: 10278/3738547


Dagnew T.M.; Silvestri C.; Slanzi D.; Poli I. A Neural Network Model for Lead Optimization of MMP12 Inhibitors , Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Science and Business Media Deutschland GmbH, vol. 12664, pp. 323-335, Convegno: ICPR 2021: Pattern Recognition. ICPR International Workshops and Challenges (ISBN 978-3-030-68798-4; 978-3-030-68799-1)
DOI 2021, Articolo in Atti di convegno - Scheda ARCA: 10278/3738884