| 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 | 189 | 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 | 111 | 2004 |
| 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 | 75 | 2013 |
| Cluster correspondence analysis M van de Velden, AI D’Enza, F Palumbo Psychometrika 82 (1), 158-185, 2017 | 51 | 2017 |
| 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 Enseņat, J Berenguer, ... Journal of neurosurgery 116 (3), 622-629, 2012 | 48 | 2012 |
| 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 | 45 | 2019 |
| 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 | 33 | 2019 |
| Iterative factor clustering of binary data A Iodice D’Enza, F Palumbo Computational Statistics 28 (2), 789-807, 2013 | 33 | 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 | 26 | 2012 |
| 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 | 12 | 2008 |
| On joint dimension reduction and clustering of categorical data A Iodice D’Enza, MV Velden, F Palumbo Analysis and modeling of complex data in behavioral and social sciences, 161-169, 2014 | 10 | 2014 |
| The idm package: incremental decomposition methods in R AI D'Enza, A Markos, D Buttarazzi Journal of Statistical Software 86, 1-24, 2018 | 7* | 2018 |
| Low-dimensional tracking of association structures in categorical data A Iodice D’Enza, A Markos Statistics and Computing 25 (5), 1009-1022, 2015 | 6 | 2015 |
| Distanceâ A Rbased clustering of mixed data MV Velden, AI D’enza, A Markos WIREs Computational Statistics, 2018 | 5 | 2018 |
| Exploratory data analysis leading towards the most interesting simple association rules A Iodice D'Enza, F Palumbo, M Greenacre Computational statistics & data analysis 52 (6), 3269-3281, 2008 | 4 | 2008 |
| Special feature: dimension reduction and cluster analysis M van de Velden, AI D’Enza, M Yamamoto Behaviormetrika 46 (2), 239-241, 2019 | 3 | 2019 |
| Incremental Generalized Canonical Correlation Analysis A Markos, AI D’Enza Analysis of Large and Complex Data, 185-194, 2016 | 3 | 2016 |
| New graphical symbolic objects representations in parallel coordinates CN Lauro, F Palumbo, AI D’Enza Between data science and applied data analysis, 288-295, 2003 | 3 | 2003 |
| A framework for the incremental update of the MCA solution A Markos, AI D’Enza Ital J Appl Stat 29 (2–3), 217-231, 2018 | 2 | 2018 |
| Clustering and Dimensionality Reduction to discover interesting patterns in Binary data F Palumbo, AI D’Enza Advances in Data Analysis, Data Handling and Business Intelligence, 45-55, 2009 | 2 | 2009 |
Francesco PalumboUniversitā degli Studi di Napoli Federico IIVerified email at unina.it
