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Information on didactic, research and institutional assignments on this page are certified by the University; more information, prepared by the professor, are available on the personal web page and in the curriculum vitae indicated on this webpage.
Information on professor
ProfessorIeva Francesca
QualificationAssociate professor full time
Belonging DepartmentDipartimento di Matematica
Scientific-Disciplinary SectorSECS-S/01 - Statistics
Curriculum VitaeDownload CV (397.0Kb - 11/09/2021)

Professor's office hours
Matematica6626WednesdayFrom 13:45
To 15:15
02.2399.4578--The scheduling of appointments by e-mail is mandatory.
Professor's personal websitehttps://sites.google.com/view/francesca-ieva/home

Data source: RE.PUBLIC@POLIMI - Research Publications at Politecnico di Milano

List of publications and reserach products for the year 2023 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Conference proceedings
A tissue-aware simulation framework for [18F]FLT spatiotemporal uptake in pancreatic ductal adenocarcinoma (Show >>)
Clustering Italian medical texts: a case study on referrals (Show >>)
Polimi at CLinkaRT: a Conditional Random Field vs a BERT-based approach (Show >>)
The FDA contribution to Health Data Science (Show >>)
Journal Articles
A general framework for penalized mixed-effects multitask learning with applications on DNA methylation surrogate biomarkers creation (Show >>)
Ask Your Data - Supporting Data Science Processes by Combining AutoML and Conversational Interfaces (Show >>)
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 (Show >>)
Dual adversarial deconfounding autoencoder for joint batch-effects removal from multi-center and multi-scanner radiomics data (Show >>)
Explainable domain transfer of distant supervised cancer subtyping model via imaging-based rules extraction (Show >>)
Learning high-order interactions for polygenic risk prediction (Show >>)
Mapping Tumor Heterogeneity via Local Entropy Assessment: Making Biomarkers Visible (Show >>)
Radiomics-Based Inter-Lesion Relation Network to Describe [18F]FMCH PET/CT Imaging Phenotypes in Prostate Cancer (Show >>)
Risk Narratives on Immigration During the COVID-19 Crisis in Italy: A Comparative Analysis of Facebook Posts Published by Politicians and by News media (Show >>)
Scaling survival analysis in healthcare with federated survival forests: A comparative study on heart failure and breast cancer genomics (Show >>)
The impact of public transport on the diffusion of COVID-19 pandemic in Lombardy during 2020 (Show >>)

List of publications and reserach products for the year 2022 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Conference proceedings
A neural network approach to survival analysis with time-dependent covariates for modelling time to cardiovascular diseases (Show >>)
AWavelet-mixed Effect Landmark Model for the Effect of Potassium and Biomarkers Profiles on Survival in Heart Failure Patients (Show >>)
Distant supervision for imaging-based cancer sub-typing in Intrahepatic Cholangiocarcinoma (Show >>)
Mixed-effects high-dimensional multivariate regression via group-lasso regularization (Show >>)
Multinomial Multilevel Models with Discrete Random Effects: a Multivariate Clustering Tool (Show >>)
Optimal timing of bone-marrow transplant in myelodysplastic syndromes through multi-state modeling and microsimulation (Show >>)
Personalised effect of discontinuing treatment in heart failure patients through multi-state modeling (Show >>)
Semi-parametric generalized linear mixed effects models for binary response for the analysis of heart failure hospitalizations (Show >>)
Journal Articles
A Deep Survival EWAS approach estimating risk profile based on pre-diagnostic DNA methylation: An application to breast cancer time to diagnosis (Show >>)
A blood DNA methylation biomarker for predicting short-term risk of cardiovascular events (Show >>)
Imaging-based representation and stratification of intra-tumor heterogeneity via tree-edit distance (Show >>)
Modelling time-varying covariates effect on survival via functional data analysis: application to the MRC BO06 trial in osteosarcoma (Show >>)
Oligoscore: a clinical score to predict overall survival in patients with oligometastatic disease treated with stereotactic body radiotherapy (Show >>)
PET/CT‑based radiomics of mass‑forming intrahepatic cholangiocarcinoma improves prediction of pathology data and survival (Show >>)
Semiparametric Multinomial Mixed-Effects Models: a University Student Profiling Tool (Show >>)

List of publications and reserach products for the year 2021 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Abstract in Rivista
PH-0656 Prediction of toxicity after prostate cancer RT: the value of a SNP-interaction polygenic risk score (Show >>)
Conference proceedings
A Functional Data Analysis Approach to Left Ventricular Remodeling Assessment (Show >>)
Cross-Subject EEG Channel Selection for the Detection of Predisposition to Alcoholism (Show >>)
Functional representation of potassium trajectories for dynamic monitoring of Heart Failure patients (Show >>)
Interpretability and interaction learning for logistic regression models (Show >>)
Learning Signal Representations for EEG Cross-Subject Channel Selection and Trial Classification (Show >>)
Modelling longitudinal latent toxicity profiles evolution in osteosarcoma patients (Show >>)
Multinomial semiparametric mixed-effects model for profiling engineering university students (Show >>)
Quantitative depth-based [18F]FMCH-avid lesion profiling in prostate cancer treatment (Show >>)
Recurrence-specific supervised graph clustering for subtyping Hodgkin Lymphoma radiomic phenotypes (Show >>)
Virtual biopsy in action: a radiomic-based model for CALI prediction (Show >>)
Journal Articles
Chemotherapy-Associated Liver Injuries: Unmet Needs and New Insights for Surgical Oncologists (Show >>)
Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity (Show >>)
Dynamic monitoring of the effects of adherence to medication on survival in Heart Failure patients: a joint modelling approach exploiting time-varying covariates (Show >>)
Early-predicting dropout of university students: an application of innovative multilevel machine learning and statistical techniques (Show >>)
Evaluating class and school effects on the joint student achievements in different subjects: a bivariate semiparametric model with random coefficients (Show >>)
Feature selection for imbalanced data with deep sparse autoencoders ensemble (Show >>)
Functional modeling of recurrent events on time‐to‐event processes (Show >>)
Generalized mixed-effects random forest: A flexible approach to predict university student dropout (Show >>)
Generalized mixed‐effects random forest: A flexible approach to predict university student dropout (Show >>)
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 (Show >>)
Performing Learning Analytics via Generalised Mixed-Effects Trees (Show >>)
Virtual Biopsy for Diagnosis of Chemotherapy-Associated Liver Injuries and Steatohepatitis: A Combined Radiomic and Clinical Model in Patients with Colorectal Liver Metastases (Show >>)
[18F]FMCH PET/CT biomarkers and similarity analysis to refine the definition of oligometastatic prostate cancer (Show >>)

List of publications and reserach products for the year 2020 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Abstract in Atti di convegno
Deep Sparse Autoencoder-based Feature Selection for SNPs validation in Prostate Cancer Radiogenomics (Show >>)
Contributions on scientific books
Modeling the Effect of Recurrent Events on Time-to-event Processes by Means of Functional Data (Show >>)
Proton-Pump Inhibitor Provider Profiling via Funnel Plots and Poisson Regression (Show >>)
Conference proceedings
A functional approach to study the relationship between dynamic covariates and survival outcomes: an application to a randomized clinical trial on osteosarcoma (Show >>)
Generalized Mixed Effects Random Forest: does Machine Learning help in predicting university student dropout? (Show >>)
Impact of time-dependent medication adherence on Heart Failure patients using a joint modelling framework (Show >>)
Including dynamic covariates in survival models via Functional Data Analysis: an application to osteosarcoma (Show >>)
Modeling the effect of dynamic covariates on time-to-event processes via Functional Data Analysis (Show >>)
PET radiomics-based lesions representation in Hodgkin lymphoma patients (Show >>)
Prediction of late radiotherapy toxicity in prostate cancer patients via joint analysis of SNPs sequences (Show >>)
Scientific Books
Eserciziario di Statistica Inferenziale (Show >>)
Journal Articles
A Deep Learning Approach Validates Genetic Risk Factors for Late Toxicity After Prostate Cancer Radiotherapy in a REQUITE Multi-National Cohort (Show >>)
Adherence to Disease-Modifying Therapy in Patients Hospitalized for HF: Findings from a Community-Based Study (Show >>)
Component-wise outlier detection methods for robustifying multivariate functional samples (Show >>)
Data mining application to healthcare fraud detection: a two-step unsupervised clustering method for outlier detection with administrative databases (Show >>)
Evaluating the effect of healthcare providers on the clinical path of heart failure patients through a semi-Markov, multi-state model (Show >>)
Joint modelling of recurrent events and survival: a Bayesian nonparametric approach (Show >>)
Methodological framework for radiomics applications in Hodgkin’s lymphoma (Show >>)
Non-parametric frailty Cox models for hierarchical time-to-event data (Show >>)
Number of lung resections performed and long-term mortality rates of patients after lung cancer surgery: evidence from an Italian investigation (Show >>)

List of publications and reserach products for the year 2019 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Traduzione di libro
Statistica Medica (Show >>)
Abstract in Atti di convegno
Data Mining Application to Healthcare Fraud Detection: Two-Step Unsupervised Clustering Method for Outlier Detection with Administrative Databases (Show >>)
Investigating the role of proteinuria in renal disease: A real-world clinical case study (Show >>)
Conference proceedings
Are Real World Data the smart way of doing Health Analytics? (Show >>)
Classification of Italian classes via bivariate semiparametric multilevel models (Show >>)
Hospital effect on 3-years-survival in patients undergone to lung tumor surgery: a real-world study. (Show >>)
Joint Models: a smart way to include functional data in healthcare analytics (Show >>)
Journal Articles
A k-means procedure based on a Mahalanobis type distance for clustering multivariate functional data (Show >>)
Adherence to recommendations and clinical outcomes of patients hospitalized for stroke: the role of the admission ward - a real-life investigation from Italy (Show >>)
Comparing methods for comparing networks (Show >>)
Semiparametric mixed-effects models for unsupervised classification of Italian schools (Show >>)
roahd Package: Robust Analysis of High Dimensional Data (Show >>)
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