Selected papers
Cavinato, L., Massi, M.C., Sollini, M., Kirienko, M., Ieva, F. (2023)
Dual Adversarial Deconfounding Autoencoder to remove batch-effect in multi-center radiomics data
Scientific Reports, 13: 18857 [Github repo]Savaré, L., Ieva, F., Corrao, G., Lora, A. (2023)
Capturing the variety of clinical pathways in patients with schizophrenic disorders through state sequence analysis .
BMC Medical Research Methodology. , 23: 174Cappozzo, A., Ieva, F., Fiorito, G. (2023)
A general framework for penalized mixed-effects multitask learning with application on DNAm biomarkers creation.
Annals of Applied Statistics, 17(4): 3257-3282 (December 2023). doi: 10.1214/23-AOAS1760Cavinato, L., Costa, G., Fiz, F., Sollini, M., Chiti, A., Torzilli, G., Ieva, F., Viganò, L. (2023)
Mapping tumor heterogeneity via local entropy assessment: making biomarkers visible.
Journal of Digital Imaging. doi: 10.1007/s10278-023-00799-9Cavinato, L., Pegoraro, M., Ragni, A., Ieva, F. (2022)
Imaging-based representation and stratification of intra-tumor heterogeneity via tree-edit distance
Scientific Reports, 12: 19607Cappozzo, A., McCrory, C., Robinson, O., Freni Sterrantino, A., Sacerdote, C., Krogh, V., Panico, S., Tumino, R.,
Iacoviello, L., Ricceri, F., Sieri, S., Chiodini, P., Kenny, R.A., O’Halloran, A., Polidoro, S., Solinas, G., Vineis, P., Ieva, F.,
Fiorito, G. (2022)
A blood DNA methylation biomarker for predicting short-term risk of cardiovascular events
Clinical Epigenetics. doi: 10.1186/s13148-022-01341-4Massi, M.C, Dominoni, L., Ieva, F., Fiorito, G. (2022)
Deep Survival EWAS approach estimating risk profile based on pre-diagnostic DNA methylation: an application to Breast Cancer time to diagnosis
PLOS COmputational Biology, 18(9): e1009959Massi, M.C., Gasperoni, F., Ieva, F., Paganoni, A.M. (2021)
Feature Selection for Imbalanced Data with Deep Sparse Autoencoders Ensemble
Statistical Analysis and Data Mining. doi: 10.1002/sam.11567Masci, C., Ieva, F., Paganoni, A.M. (2021)
Semiparametric Multinomial Mixed-Effects Models: a University Student Profiling Tool
Annals of Applied Statistics. To appearSpreafico, M., Ieva, F. (2021)
Functional modelling of recurrent events on time-to-event processes
Biometrical Journal, 63(5): 948–967 doi: 10.1002/bimj.202000374Spreafico, M.; Ieva, F. (2021)
Dynamic monitoring of the effects of adherence to medication on survival in Heart Failure patients: a joint modelling approach exploiting time-varying covariates.
Biometrical Journal , 63(2) Special Issue: Novel Aspects in Biostatistics: 305-322Massi, M., Gasperoni, F., Ieva, F. et al. for the REQUITE consorzium (2020)
A deep learning approach validates genetic risk factors for late toxicity after prostate cancer radiotherapy in a REQUITE multi-national cohort
Frontiers in Oncology - section Radiation Oncology, 10: 2033. doi: 10.3389/fonc.2020.541281 ISSN=2234-943XMassi, M., Ieva, F., Lettieri, E. (2020)
Data Mining Application to Healthcare Fraud Detection: A Two-Step Unsupervised Clustering Model for Outlier Detection with Administrative Databases.
BMC Medical Informatics and Decision Making, 20 (1): 1-11Sollini, M., Kirienko, M., Cavinato, L., Ricci, F., Biroli, M., Ieva, F., Calderoni, L., Tabacchi, E., Nanni, C., Zinzani, P.L., Fanti, S., Guidetti, A., Alessi, A., Corradini, P., Seregni, E., Carlo-Stella, C., Chiti, A. (2020)
Methodological framework for radiomics applications in Hodgkin's Lymphoma
European Journal of Hybrid Imaging. 4: 1-17Gasperoni, F.; Ieva, F.; Paganoni, A.M.; Jackson, C.; Sharples, L. (2020)
Evaluating the effect of healthcare providers on the clinical path of Heart Failure patients through a novel semi-Markov multi-state model.
BMC Health Services Research. 20 (1): 1-11Paulon, G., De Iorio, M, Guglielmi, A., Ieva, F. (2020, online first 2018)
Joint modelling of recurrent events and survival: a Bayesian nonparametric approach.
Biostatistics 21 (1), 1-14
Tantardini, M., Ieva, F., Tajoli, L., Piccardi, C. (2019)
Comparing methods for comparing networks
Scientific Reports, 9, 17557 doi:10.1038/s41598-019-53708-y
Gasperoni, F., Ieva, F. Paganoni, A.M., Jackson C., Sharples L.D. (2019)
Nonparametric frailty Cox models for hierarchical time-to-event data
Biostatistics. doi: 10.1093/biostatistics/kxy071
Masci, C., Paganoni, A.M., Ieva, F. (2019)
Semi-parametric mixed-e ects models for unsupervised classiffcation of Italian schools
Journal of the Royal Statistical Society - series A, 182(4): 1313–1342
Ekin, T., Ieva, F., Ruggeri, F., Soyer, R. (2018)
Statistical Medical Fraud Assessment: Exposition to an Emerging Field.
International Statistical Review, 86 (3): 379–402Gasperoni, F., Ieva, F., Barbati, G., Scagnetto, A., Iorio, A., Sinagra, G., Di Lenarda, A. (2017)
Multi state modelling of Heart Failure care path: a population-based investigation from Italy.
PlosOne 12(6): e0179176 --- highlight on Biomedical Advances
Ieva, F., Jackson, C.H., Sharples, L.D. (2017, online first 2015)
Multi-State modelling of repeated hospitalisation and death in patients with Heart Failure: the use of large administrative databases in clinical epidemiology.
Statistical Methods in Medical Research, 26 (3): 1350-1372
Frigerio, M., Mazzali, C., Paganoni, A.M., Ieva, F., Barbieri, P., Maistrello, M., Agostoni, O., Masella, C., Scalvini, S. (2017)
Trends in heart failure hospitalizations, patient characteristics, in-hospital and 1-year mortality: a population study, from 2000 to 2012 in Lombardy.
International Journal of Cardiology, 236: 310–314. doi:10.1016/j.ijcard.2017.02.052
Ekin, T., Ieva, F., Ruggeri, F., Soyer, R. (2017)
On the Use of the Concentration Function in Medical Fraud Assessment.
The American Statistician, 71(3): 236-241
Ieva, F., Paganoni, A.M., Pietrabissa, T. (2017, online first 2016)
Dynamic clustering of hazard functions: an application to disease progression in chronic heart failure.
Health Care Management of Science, 20: 353–364.
Mazzali, C., Paganoni, A.M., Ieva, F., Masella, C., ..., Scalvini, S., Frigerio, M. (2016)
Methodological issues on the use of administrative data in healthcare research: the case of heart failure hospitalizations in Lombardy Region, 2000 to 2012.
BMC Health Services Research, 16 (1): 234 doi: 10.1186/s12913-016-1489-0
Ieva, F., Paganoni, A.M. (2016, online first 2013).
Risk Prediction for Myocardial Infarction via Generalized Functional Regression Models.
Statistical Methods in Medical Research. 25 (4): 1648-1660
Tarabelloni, N., Ieva, F., Paganoni, A.M., Biasi, R. (2015)
Use of depth measure for multivariate functional data in disease prediction: an application to electrocardiograph signals.
International Journal of Biostatistics, 11(2), 189–201.
Ieva, F., Paganoni, A.M. (2015)
Detecting and Visualizing Outliers in Provider Profiling via Funnel Plots and Mixed Effect Models.
Health Care Management Science, 18(2): 166–172.
Ieva, F., Gale, C.P., Sharples, L.D. (2015)
Contemporary roles of registries in clinical cardiology: when do we need randomized trials?
Expert Review of Cardiovascular Therapy, 12 (12): 1383-1386
Guglielmi, A., Ieva, F., Paganoni, A.M., Ruggeri, F., Soriano, J. (2014)
Semiparametric Bayesian modeling for the classification of patients with high observed survival probabilities.
Journal of the Royal Statistical Society - Series C, 63 (1): 25-46
Ieva, F., Paganoni, A.M., Pigoli, D., Vitelli, V. (2013).
Multivariate functional clustering for the analysis of ECG curves morphology.
Journal of the Royal Statistical Society – Series C, 62(3): 401-418
Azzimonti, L., Ieva, F., Paganoni, A.M. (2013)
Nonlinear nonparametric mixed-effects models for unsupervised classification
Computational Statistics, 28:1549–1570. doi:10.1007/s00180-012-0366-5
Baraldo, S., Ieva, F., Paganoni, A.M., Vitelli, V. (2013)
Generalized functional linear models for recurrent events: an application to re-admission processes in heart failure patients Scandinavian Journal of Statistics, 40(3): 403-416, September 2013
Ieva, F., Paganoni, A.M.. (2013).
Depth Measures for Multivariate Functional Data.
Communication in Statistics – Theory and Methods, 42(7): 1265-1276.
Di Lullo, G., Ieva, F., Longhi, R., Paganoni, A.M., Protti, M.P. (2012)
Estimating point and interval frequency of antigen-specific CD4+ T cells based on short in vitro expansion and improved Poisson distribution analysis.
PLoS One, 7(8). e42340. Epub 2012 Aug 7.
Grieco, N., Corrada, E., Sesana, G., Ieva, F., Paganoni, A.M., Marzegalli, M. (2012).
Mort ality and ST resolution in patients admitted with STEMI: the MOMI survey of emergency service experience in a complex urban area.
European Heart Journal: Acute Cardiovascular Care, 1(3), 192–199.
Grieco, N., Ieva, F., Paganoni, A.M. (2012)
Performance assessment using mixed effects models: a case study on coronary patient care.
IMA Journal of Management Mathematics, 23(2), 117-131