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Nicola Lazzarini
Nicola Lazzarini
Verified email at ncl.ac.uk - Homepage
Title
Cited by
Cited by
Year
Coupling different methods for overcoming the class imbalance problem
L Nanni, C Fantozzi, N Lazzarini
Neurocomputing 158, 48-61, 2015
1392015
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
1192015
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
812017
RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers
N Lazzarini, J Bacardit
BMC bioinformatics 18, 1-22, 2017
202017
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
142014
Functional networks inference from rule-based machine learning models
N Lazzarini, P Widera, S Williamson, R Heer, N Krasnogor, J Bacardit
BioData mining 9, 1-23, 2016
122016
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
92021
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
82022
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
82015
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
62013
Characterising the influence of rule-based knowledge representations in biological knowledge extraction from transcriptomics data
S Baron, N Lazzarini, J Bacardit
Applications of Evolutionary Computation: 20th European Conference …, 2017
52017
Tecniche di apprendimento automatico per l'identificazione dell'iperaldosteronismo primario
N Lazzarini
12012
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
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