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Tipologia Anno Titolo Titolo inglese Autore File
Lauree magistrali 2025 Confronto di tecniche basate sul Propensity Score per stimare l'effetto del trattamento: uno studio comparativo sul trial LEADER Comparison of Propensity Score-based techniques for estimating treatment effect: a comparative study on the LEADER trial LATINO, MATTEO
Lauree magistrali 2024 Deep Sequence Modelling of Non-Stationary Disease Progression in Amyotrophic Lateral Sclerosis from Simulated Longitudinal Data Deep Sequence Modelling of Non-Stationary Disease Progression in Amyotrophic Lateral Sclerosis from Simulated Longitudinal Data TRAJKOVSKI, FILIP
Lauree magistrali 2025 Evaluating the Utility of Synthetic Data generated using Bayesian Networks: an Amyotrophic Lateral Sclerosis Application Evaluating the Utility of Synthetic Data generated using Bayesian Networks: an Amyotrophic Lateral Sclerosis Application SVETOVA, KRISTINA
Lauree magistrali 2025 Il modello di Cox a covariate e coefficienti tempo-varianti: benchmark e applicazioni The Cox model with time varying covariates and time varying coefficients: benchmarks and applications MARCHESONI, PIETRO
Lauree magistrali 2024 Leveraging Bayesian Networks to explore the relationships between maternal characteristics, continuous glucose monitoring data, and neonatal outcomes in pregnancies complicated by gestational diabetes Leveraging Bayesian Networks to explore the relationships between maternal characteristics, continuous glucose monitoring data, and neonatal outcomes in pregnancies complicated by gestational diabetes CATANUSO, MARCO
Lauree magistrali 2024 Online Machine Learning for Survival Prediction in Amyotrophic Lateral Sclerosis Online Machine Learning for Survival Prediction in Amyotrophic Lateral Sclerosis ZAGARIA, MARIA LAURA
Lauree magistrali 2024 Simulating the Long-Term Outcomes of Diabetes: Dynamic Bayesian Networks Applied to the LEADER Clinical Trial Simulating the Long-Term Outcomes of Diabetes: Dynamic Bayesian Networks Applied to the LEADER Clinical Trial GONZATO, NOEMI
Lauree magistrali 2023 SVILUPPO DI MODELLI DI DEEP LEARNING PER LA PREDIZIONE DEI RELAPSE IN PAZIENTI AFFETTI DA SCLEROSI MULTIPLA A PARTIRE DA DATI CLINICI E AMBIENTALI DEVELOPMENT OF DEEP LEARNING MODELS FOR THE PREDICTION OF RELAPSES IN PATIENTS WITH MULTIPLE SCLEROSIS VIA CLINICAL AND ENVIRONMENTAL DATA MILANI, ANNA
Lauree magistrali 2024 Sviluppo di modelli predittivi della progressione della sclerosi multipla: confronto tra tecniche per il bilanciamento delle classi Development of predictive models of multiple sclerosis progression: comparison of class balancing techniques OTTONE, MARIA
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