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Le informazioni sulla didattica, sulla ricerca e sui compiti istituzionali riportate in questa pagina sono certificate dall'Ateneo; ulteriori informazioni, redatte a cura del docente, sono disponibili sulla pagina web personale e nel curriculum vitae indicati nella scheda.
Informazioni sul docente
DocenteIeva Francesca
QualificaProfessore associato a tempo pieno
Dipartimento d'afferenzaDipartimento di Matematica
Settore Scientifico DisciplinareSECS-S/01 - Statistica
Curriculum VitaeScarica il CV (397.0Kb - 11/09/2021)

Orario di ricevimento
Matematica6626MercoledìDalle 13:45
Alle 15:15
02.2399.4578--E' necessario concordare anticipatamente i ricevimenti tramite e-mail.
Pagina web redatta a cura del docentehttps://sites.google.com/view/francesca-ieva/home

Fonte dati: RE.PUBLIC@POLIMI - Research Publications at Politecnico di Milano

Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2024
Nessun prodotto attualmente registrato nell'anno 2024

Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2023 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Contributo in Atti di convegno
A tissue-aware simulation framework for [18F]FLT spatiotemporal uptake in pancreatic ductal adenocarcinoma (Mostra >>)
Clustering Italian medical texts: a case study on referrals (Mostra >>)
Polimi at CLinkaRT: a Conditional Random Field vs a BERT-based approach (Mostra >>)
The FDA contribution to Health Data Science (Mostra >>)
Articoli su riviste
A general framework for penalized mixed-effects multitask learning with applications on DNA methylation surrogate biomarkers creation (Mostra >>)
Ask Your Data - Supporting Data Science Processes by Combining AutoML and Conversational Interfaces (Mostra >>)
Detecting early signals of COVID-19 outbreaks in 2020 in small areas by monitoring healthcare utilisation databases: first lessons learned from the Italian Alert_CoV project (Mostra >>)
Dual adversarial deconfounding autoencoder for joint batch-effects removal from multi-center and multi-scanner radiomics data (Mostra >>)
Explainable domain transfer of distant supervised cancer subtyping model via imaging-based rules extraction (Mostra >>)
Learning high-order interactions for polygenic risk prediction (Mostra >>)
Mapping Tumor Heterogeneity via Local Entropy Assessment: Making Biomarkers Visible (Mostra >>)
Radiomics-Based Inter-Lesion Relation Network to Describe [18F]FMCH PET/CT Imaging Phenotypes in Prostate Cancer (Mostra >>)
Risk Narratives on Immigration During the COVID-19 Crisis in Italy: A Comparative Analysis of Facebook Posts Published by Politicians and by News media (Mostra >>)
Scaling survival analysis in healthcare with federated survival forests: A comparative study on heart failure and breast cancer genomics (Mostra >>)
The impact of public transport on the diffusion of COVID-19 pandemic in Lombardy during 2020 (Mostra >>)

Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2022 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Contributo in Atti di convegno
A neural network approach to survival analysis with time-dependent covariates for modelling time to cardiovascular diseases (Mostra >>)
AWavelet-mixed Effect Landmark Model for the Effect of Potassium and Biomarkers Profiles on Survival in Heart Failure Patients (Mostra >>)
Distant supervision for imaging-based cancer sub-typing in Intrahepatic Cholangiocarcinoma (Mostra >>)
Mixed-effects high-dimensional multivariate regression via group-lasso regularization (Mostra >>)
Multinomial Multilevel Models with Discrete Random Effects: a Multivariate Clustering Tool (Mostra >>)
Optimal timing of bone-marrow transplant in myelodysplastic syndromes through multi-state modeling and microsimulation (Mostra >>)
Personalised effect of discontinuing treatment in heart failure patients through multi-state modeling (Mostra >>)
Semi-parametric generalized linear mixed effects models for binary response for the analysis of heart failure hospitalizations (Mostra >>)
Articoli su riviste
A Deep Survival EWAS approach estimating risk profile based on pre-diagnostic DNA methylation: An application to breast cancer time to diagnosis (Mostra >>)
A blood DNA methylation biomarker for predicting short-term risk of cardiovascular events (Mostra >>)
Imaging-based representation and stratification of intra-tumor heterogeneity via tree-edit distance (Mostra >>)
Modelling time-varying covariates effect on survival via functional data analysis: application to the MRC BO06 trial in osteosarcoma (Mostra >>)
Oligoscore: a clinical score to predict overall survival in patients with oligometastatic disease treated with stereotactic body radiotherapy (Mostra >>)
PET/CT‑based radiomics of mass‑forming intrahepatic cholangiocarcinoma improves prediction of pathology data and survival (Mostra >>)
Semiparametric Multinomial Mixed-Effects Models: a University Student Profiling Tool (Mostra >>)

Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2021 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Abstract in Rivista
PH-0656 Prediction of toxicity after prostate cancer RT: the value of a SNP-interaction polygenic risk score (Mostra >>)
Contributo in Atti di convegno
A Functional Data Analysis Approach to Left Ventricular Remodeling Assessment (Mostra >>)
Cross-Subject EEG Channel Selection for the Detection of Predisposition to Alcoholism (Mostra >>)
Functional representation of potassium trajectories for dynamic monitoring of Heart Failure patients (Mostra >>)
Interpretability and interaction learning for logistic regression models (Mostra >>)
Learning Signal Representations for EEG Cross-Subject Channel Selection and Trial Classification (Mostra >>)
Modelling longitudinal latent toxicity profiles evolution in osteosarcoma patients (Mostra >>)
Multinomial semiparametric mixed-effects model for profiling engineering university students (Mostra >>)
Quantitative depth-based [18F]FMCH-avid lesion profiling in prostate cancer treatment (Mostra >>)
Recurrence-specific supervised graph clustering for subtyping Hodgkin Lymphoma radiomic phenotypes (Mostra >>)
Virtual biopsy in action: a radiomic-based model for CALI prediction (Mostra >>)
Articoli su riviste
Chemotherapy-Associated Liver Injuries: Unmet Needs and New Insights for Surgical Oncologists (Mostra >>)
Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity (Mostra >>)
Dynamic monitoring of the effects of adherence to medication on survival in Heart Failure patients: a joint modelling approach exploiting time-varying covariates (Mostra >>)
Early-predicting dropout of university students: an application of innovative multilevel machine learning and statistical techniques (Mostra >>)
Evaluating class and school effects on the joint student achievements in different subjects: a bivariate semiparametric model with random coefficients (Mostra >>)
Feature selection for imbalanced data with deep sparse autoencoders ensemble (Mostra >>)
Functional modeling of recurrent events on time‐to‐event processes (Mostra >>)
Generalized mixed-effects random forest: A flexible approach to predict university student dropout (Mostra >>)
Novel longitudinal Multiple Overall Toxicity (MOTox) score to quantify adverse events experienced by patients during chemotherapy treatment: a retrospective analysis of the MRC BO06 trial in osteosarcoma (Mostra >>)
Performing Learning Analytics via Generalised Mixed-Effects Trees (Mostra >>)
Virtual Biopsy for Diagnosis of Chemotherapy-Associated Liver Injuries and Steatohepatitis: A Combined Radiomic and Clinical Model in Patients with Colorectal Liver Metastases (Mostra >>)
[18F]FMCH PET/CT biomarkers and similarity analysis to refine the definition of oligometastatic prostate cancer (Mostra >>)

Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2020 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Abstract in Atti di convegno
Deep Sparse Autoencoder-based Feature Selection for SNPs validation in Prostate Cancer Radiogenomics (Mostra >>)
Contributi su volumi (Capitolo o Saggio)
Modeling the Effect of Recurrent Events on Time-to-event Processes by Means of Functional Data (Mostra >>)
Proton-Pump Inhibitor Provider Profiling via Funnel Plots and Poisson Regression (Mostra >>)
Contributo in Atti di convegno
A functional approach to study the relationship between dynamic covariates and survival outcomes: an application to a randomized clinical trial on osteosarcoma (Mostra >>)
Generalized Mixed Effects Random Forest: does Machine Learning help in predicting university student dropout? (Mostra >>)
Impact of time-dependent medication adherence on Heart Failure patients using a joint modelling framework (Mostra >>)
Including dynamic covariates in survival models via Functional Data Analysis: an application to osteosarcoma (Mostra >>)
Modeling the effect of dynamic covariates on time-to-event processes via Functional Data Analysis (Mostra >>)
PET radiomics-based lesions representation in Hodgkin lymphoma patients (Mostra >>)
Prediction of late radiotherapy toxicity in prostate cancer patients via joint analysis of SNPs sequences (Mostra >>)
Monografie o trattati scientifici
Eserciziario di Statistica Inferenziale (Mostra >>)
Articoli su riviste
A Deep Learning Approach Validates Genetic Risk Factors for Late Toxicity After Prostate Cancer Radiotherapy in a REQUITE Multi-National Cohort (Mostra >>)
Adherence to Disease-Modifying Therapy in Patients Hospitalized for HF: Findings from a Community-Based Study (Mostra >>)
Component-wise outlier detection methods for robustifying multivariate functional samples (Mostra >>)
Data mining application to healthcare fraud detection: a two-step unsupervised clustering method for outlier detection with administrative databases (Mostra >>)
Evaluating the effect of healthcare providers on the clinical path of heart failure patients through a semi-Markov, multi-state model (Mostra >>)
Joint modelling of recurrent events and survival: a Bayesian nonparametric approach (Mostra >>)
Methodological framework for radiomics applications in Hodgkin’s lymphoma (Mostra >>)
Non-parametric frailty Cox models for hierarchical time-to-event data (Mostra >>)
Number of lung resections performed and long-term mortality rates of patients after lung cancer surgery: evidence from an Italian investigation (Mostra >>)
manifesti v. 3.5.13 / 3.5.13
Area Servizi ICT