Anna Maria Paganoni
Polytechnic University of Milan
Nonparametric statisticsStatisticsBayesian probabilityCovariateMachine learningData miningInternal medicineEconometricsArtificial intelligenceMultivariate statisticsPattern recognitionImmunologyHeart failureContext (language use)Mixed effectsMathematicsComputer scienceMyocardial infarctionMedicineCluster analysis
175Publications
18H-index
1,172Citations
Publications 173
Newest
#1Chiara Masci (Polytechnic University of Milan)H-Index: 5
#2Francesca Ieva (Polytechnic University of Milan)H-Index: 14
Last. Anna Maria Paganoni (Polytechnic University of Milan)H-Index: 18
view all 4 authors...
This paper proposes an innovative statistical method to measure the impact of the class/school on student achievements in multiple subjects. We propose a semiparametric model for a bivariate response variable with random coefficients, that are assumed to follow a discrete distribution with an unknown number of support points, together with an Expectation-Maximization algorithm—called BSPEM algorithm—to estimate its parameters. In the case study, we apply the BSPEM algorithm to data about Italian...
Source
#1Nicola Rares Franco (Ghent University Hospital)
#1Nicola Rares Franco (Ghent University Hospital)H-Index: 1
Last. Tiziana RancatiH-Index: 27
view all 43 authors...
AIM To identify the effect of single nucleotide polymorphism (SNP) interactions on the risk of toxicity following radiotherapy (RT) for prostate cancer (PCa) and propose a new method for polygenic risk score incorporating SNP-SNP interactions (PRSi). MATERIALS AND METHODS Analysis included the REQUITE PCa cohort that received external beam RT and was followed for 2 years. Late toxicity endpoints were: rectal bleeding, urinary frequency, haematuria, nocturia, decreased urinary stream. Among 43 li...
Source
#1Michela Carlotta Massi (Polytechnic University of Milan)H-Index: 2
#2Francesca IevaH-Index: 14
Last. Anna Maria PaganoniH-Index: 18
view all 4 authors...
Class imbalance is a common issue in many domain applications of learning algorithms. Oftentimes, in the same domains it is much more relevant to correctly classify and profile minority class observations. This need can be addressed by Feature Selection (FS), that offers several further advantages, s.a. decreasing computational costs, aiding inference and interpretability. However, traditional FS techniques may become sub-optimal in the presence of strongly imbalanced data. To achieve FS advanta...
#1Massimo Pellagatti (Polytechnic University of Milan)H-Index: 1
#2Chiara Masci (Polytechnic University of Milan)H-Index: 5
Last. Anna Maria Paganoni (Polytechnic University of Milan)H-Index: 18
view all 4 authors...
1 CitationsSource
#1Michela Carlotta Massi (Polytechnic University of Milan)H-Index: 2
Last. Paolo ZuninoH-Index: 28
view all 6 authors...
Logistic Regression (LR) is a widely used statistical method in empirical binary classification studies. However, real-life scenarios oftentimes share complexities that prevent from the use of the as-is LR model, and instead highlight the need to include high-order interactions to capture data variability. This becomes even more challenging because of: (i) datasets growing wider, with more and more variables; (ii) studies being typically conducted in strongly imbalanced settings; (iii) samples g...
Abstract Background This study evaluates, in a real-world setting, to what extent the recommended therapies by international guidelines, are prescribed after a first hospitalization for heart failure (HF), and to analyse adherence and persistence, and the effect of treatment adherence on mortality and re-hospitalization. Methods From the Lombardy healthcare administrative database, we analysed patients discharged after their incident HF, from 2000 to 2012. Adherence was defined as the proportion...
1 CitationsSource
#1Maurizio ColecchiaH-Index: 31
#2Alessia BertolottiH-Index: 3
Last. G.P. DagradaH-Index: 12
view all 9 authors...
AIMS The aim was to investigate the morphological and molecular characteristics of Leydig cell tumors of the testis (LCT) for the identification of cases that may metastasize. METHODS AND RESULTS Six parameters for a predictive model of the metastatic risk were evaluated in 37 benign and 14 malignant in LCTs of the testis (LCT scaled score = LeSS). The tumor size (benign LCTs: mean 1.33 cm, malignant cases: mean 4.4 cm) (P <0.001) and other five parameters (infiltrative margins, necrosis, vascul...
Source
#1Andrea Martino (Polytechnic University of Milan)H-Index: 2
#2Giuseppina Guatteri (Polytechnic University of Milan)H-Index: 9
Last. Anna Maria Paganoni (Polytechnic University of Milan)H-Index: 18
view all 3 authors...
Abstract In this paper we extend the usual Hidden Markov Models framework, where the observed objects are univariate or multivariate data, to the case of functional data, by modeling the temporal structure of a system of multivariate curves evolving in time.
Source
#1Michela Carlotta Massi (Polytechnic University of Milan)H-Index: 2
#2Francesca Gasperoni (Medical Research Council)
Last. Tiziana RancatiH-Index: 27
view all 46 authors...
Background: REQUITE (validating pREdictive models and biomarkers of radiotherapy toxicity to reduce side effects and improve QUalITy of lifE in cancer survivors) is an international prospective cohort study. The purpose of this project was to analyse a cohort of patients recruited into REQUITE using a deep learning algorithm to identify patient-specific features associated with the development of toxicity, and test the approach by attempting to validate previously published genetic risk factors....
2 CitationsSource
#2Ana Arribas-GilH-Index: 7
Last. Juan RomoH-Index: 17
view all 5 authors...