Principal component analysis M Greenacre, PJF Groenen, T Hastie, AI d’Enza, A Markos, E Tuzhilina Nature Reviews Methods Primers 2 (1), 100, 2022 | 808 | 2022 |
The endoscopic endonasal approach for the management of craniopharyngiomas: a series of 103 patients LM Cavallo, G Frank, P Cappabianca, D Solari, D Mazzatenta, A Villa, ... Journal of neurosurgery 121 (1), 100-113, 2014 | 269 | 2014 |
Sellar repair with fibrin sealant and collagen fleece after endoscopic endonasal transsphenoidal surgery P Cappabianca, LM Cavallo, V Valente, I Romano, AI D'Enza, F Esposito, ... Surgical neurology 62 (3), 227-233, 2004 | 125 | 2004 |
Distance‐based clustering of mixed data M Van de Velden, A Iodice D'Enza, A Markos Wiley Interdisciplinary Reviews: Computational Statistics 11 (3), e1456, 2019 | 122 | 2019 |
Cluster correspondence analysis M Van de Velden, AI D’Enza, F Palumbo Psychometrika 82 (1), 158-185, 2017 | 96 | 2017 |
Endoscopic endonasal transsphenoidal removal of recurrent and regrowing pituitary adenomas: experience on a 59-patient series LM Cavallo, D Solari, A Tasiou, F Esposito, M de Angelis, AI D'Enza, ... World neurosurgery 80 (3-4), 342-350, 2013 | 82 | 2013 |
Beyond tandem analysis: Joint dimension reduction and clustering in R A Markos, AI D'Enza, M van de Velden Journal of Statistical Software 91, 1-24, 2019 | 80 | 2019 |
The “suprasellar notch,” or the tuberculum sellae as seen from below: definition, features, and clinical implications from an endoscopic endonasal perspective M de Notaris, D Solari, LM Cavallo, AI D'Enza, J Enseñat, J Berenguer, ... Journal of neurosurgery 116 (3), 622-629, 2012 | 66 | 2012 |
Iterative factor clustering of binary data A Iodice D’Enza, F Palumbo Computational Statistics 28, 789-807, 2013 | 39 | 2013 |
Multiple correspondence analysis for the quantification and visualization of large categorical data sets AI D’Enza, M Greenacre Advanced statistical methods for the analysis of large data-sets, 453-463, 2012 | 34 | 2012 |
Publisher correction: principal component analysis M Greenacre, P Groenen, T Hastie, A IODICE D'ENZA, A Markos, ... Nature Reviews Methods Primers 3 (1), 2023 | 14 | 2023 |
Special feature: dimension reduction and cluster analysis M van de Velden, AI D’Enza, M Yamamoto Behaviormetrika 46, 239-241, 2019 | 12 | 2019 |
’Enza A, Markos A M Van de Velden, D Iodice Distance‑based clustering of mixed data. WIREs Comput Stat 11 (3), e1456, 2019 | 11 | 2019 |
Exploratory data analysis leading towards the most interesting simple association rules AI D’enza, F Palumbo, M Greenacre Computational Statistics & Data Analysis 52 (6), 3269-3281, 2008 | 11 | 2008 |
’Enza A, Van de Velden M (2019). clustrd: Methods for Joint Dimension Reduction and Clustering A Markos, D Iodice R package version 1 (0), 0 | 11 | |
On joint dimension reduction and clustering of categorical data A Iodice D’Enza, M Van de Velden, F Palumbo Analysis and modeling of complex data in behavioral and social sciences, 161-169, 2014 | 10 | 2014 |
Predicting the early visual outcomes in sellar-suprasellar lesions compressing the chiasm: the role of SD-OCT series of 20 patients operated via endoscopic endonasal approach D Solari, G Cennamo, F Amoroso, F Frio, P Donna, AI D'Enza, ... Journal of neurosurgical sciences 66 (4), 362-370, 2022 | 9 | 2022 |
A general framework for implementing distances for categorical variables M Van De Velden, AI D’Enza, A Markos, C Cavicchia Pattern Recognition 153, 110547, 2024 | 8 | 2024 |
The idm package: incremental decomposition methods in R AI D'Enza, A Markos, D Buttarazzi Journal of Statistical Software 86, 1-24, 2018 | 8 | 2018 |
Low-dimensional tracking of association structures in categorical data A Iodice D’Enza, A Markos Statistics and Computing 25, 1009-1022, 2015 | 6 | 2015 |