| Coupling different methods for overcoming the class imbalance problem L Nanni, C Fantozzi, N Lazzarini Neurocomputing 158, 48-61, 2015 | 123 | 2015 |
| Prediction of human population responses to toxic compounds by a collaborative competition F Eduati, LM Mangravite, T Wang, H Tang, JC Bare, R Huang, T Norman, ... Nature biotechnology 33 (9), 933-940, 2015 | 106 | 2015 |
| A machine learning approach for the identification of new biomarkers for knee osteoarthritis development in overweight and obese women N Lazzarini, J Runhaar, AC Bay-Jensen, CS Thudium, ... Osteoarthritis and cartilage 25 (12), 2014-2021, 2017 | 54 | 2017 |
| RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers N Lazzarini, J Bacardit BMC bioinformatics 18 (1), 1-22, 2017 | 17 | 2017 |
| Functional networks inference from rule-based machine learning models N Lazzarini, P Widera, S Williamson, R Heer, N Krasnogor, J Bacardit BioData mining 9 (1), 1-23, 2016 | 8 | 2016 |
| Hard Data Analytics Problems Make for Better Data Analysis Algorithms: Bioinformatics as an Example J Bacardit, P Widera, N Lazzarini, N Krasnogor Big Data 2 (3), 164--176, 2014 | 8 | 2014 |
| Heterogeneous machine learning system for improving the diagnosis of primary aldosteronism N Lazzarini, L Nanni, C Fantozzi, A Pietracaprina, G Pucci, TM Seccia, ... Pattern Recognition Letters 65, 124-130, 2015 | 6 | 2015 |
| Heterogeneous Ensembles for the Missing Feature Problem L Nanni, S Brahnam, C Fantozzi, N Lazzarini 2013 Annual Meeting of the Northeast Decision Sciences Institute,New York, 2013 | 6 | 2013 |
| Characterising the influence of rule-based knowledge representations in biological knowledge extraction from transcriptomics data S Baron, N Lazzarini, J Bacardit European Conference on the Applications of Evolutionary Computation, 125-141, 2017 | 4 | 2017 |
| Identification of CNGB1 as a Predictor of Response to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer AC Hepburn, N Lazzarini, R Veeratterapillay, L Wilson, J Bacardit, R Heer Cancers 13 (15), 3903, 2021 | 1 | 2021 |
| Tecniche di apprendimento automatico per l'identificazione dell'iperaldosteronismo primario N Lazzarini | 1 | 2012 |
| A machine learning model on Real World Data for predicting progression to Acute Respiratory Distress Syndrome (ARDS) among COVID-19 patients N Lazzarini, A Filippoupolitis, P Manzione, H Eleftherohorinou PloS one 17 (7), e0271227, 2022 | | 2022 |
| A machine learning pipeline for the identification of predictive biomarkers and its application to knee osteoarthritis N Lazzarini, J Bacardit F1000Research 6, 2017 | | 2017 |
| Knowledge extraction from biomedical data using machine learning N Lazzarini Newcastle University, 2017 | | 2017 |
| Heterogeneous Machine Learning System for Diagnosing Primary Aldosteronism N Lazzarini, L Nanni, C Fantozzi, A Pietracaprina, G Pucci, MT Seccia, ... Journal of Hypertension 31 (e-Supplement A), e409, 2013 | | 2013 |
Loris NanniDipartimento di Ingegneria dell'Informazione - University of Padova (Padua) - ItalyVerified email at unipd.it
