Importance of Recalibrating Models for Type 2 Diabetes Onset Prediction: Application of the Diabetes Population Risk Tool on the Health and Retirement Study. - Martina Vettoretti; Enrico Longato; Barbara Di Camillo; Andrea Facchinetti (EMBC, 2018)

Glycaemic variability-based classification of impaired glucose tolerance vs. type 2 diabetes using continuous glucose monitoring data. - Enrico Longato; Giada Acciaroli; Andrea Facchinetti; Liisa Hakaste; Tuomi Tiinamaija; Alberto Maran; Giovanni Sparacino (Comput. Biol. Medicine, 2018)

Detecting Undiagnosed Diabetes: Proof-of-Concept Based on the Health-Information Exchange System of the Veneto Region (North-East Italy). - Enrico Longato; Barbara Di Camillo; Giovanni Sparacino; Claudio Saccavini; Arianna Cocchiglia; Lara Tramontan; Gian Paolo Fadini (EMBC, 2019)

A practical perspective on the concordance index for the evaluation and selection of prognostic time-to-event models. - Enrico Longato; Martina Vettoretti; Barbara Di Camillo (J. Biomed. Informatics, 2020)

Recurrent Neural Network to Predict Renal Function Impairment in Diabetic Patients via Longitudinal Routine Check-up Data. - Enrico Longato; Gian Paolo Fadini; Giovanni Sparacino; Angelo Avogaro; Barbara Di Camillo (AIME, 2021)

Comparing the Predictive Power of Heart Failure Hospitalisation Risk Scores in the Diabetic Outpatient Clinic and Primary Care Settings. - Alessandro Guazzo; Alessandro Battaggia; Enrico Longato; Bruno Franco-Novelletto; Angelo Avogaro; Gian Paolo Fadini; Maurizio Cancian; Barbara Di Camillo; Giovanni Sparacino; Massimo Fusello (BIBM, 2021)

A Deep Learning Approach to Predict Diabetes' Cardiovascular Complications From Administrative Claims. - Enrico Longato; Gian Paolo Fadini; Giovanni Sparacino; Angelo Avogaro; Lara Tramontan; Barbara Di Camillo (IEEE J. Biomed. Health Informatics, 2021)

Overview of iDPP@CLEF 2022: The Intelligent Disease Progression Prediction Challenge. - Alessandro Guazzo; Isotta Trescato; Enrico Longato; Enidia Hazizaj; Dennis Dosso; Guglielmo Faggioli; Giorgio Maria Di Nunzio; Gianmaria Silvello; Martina Vettoretti; Erica Tavazzi; Chiara Roversi; Piero Fariselli; et al. (CLEF (Working Notes), 2022)

Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2022. - Alessandro Guazzo; Isotta Trescato; Enrico Longato; Enidia Hazizaj; Dennis Dosso; Guglielmo Faggioli; Giorgio Maria Di Nunzio; Gianmaria Silvello; Martina Vettoretti; Erica Tavazzi; Chiara Roversi; Piero Fariselli; et al. (CLEF, 2022)

Baseline Machine Learning Approaches To Predict Amyotrophic Lateral Sclerosis Disease Progression. - Isotta Trescato; Alessandro Guazzo; Enrico Longato; Enidia Hazizaj; Chiara Roversi; Erica Tavazzi; Martina Vettoretti; Barbara Di Camillo (CLEF (Working Notes), 2022)

Explainable Deep-Learning Model Reveals Past Cardiovascular Disease in Patients with Diabetes Using Free-Form Visit Reports. - Alessandro Guazzo; Enrico Longato; Gian Paolo Fadini; Mario Luca Morieri; Giovanni Sparacino; Barbara Di Camillo (LOD (1), 2022)

Time-series analysis of multidimensional clinical-laboratory data by dynamic Bayesian networks reveals trajectories of COVID-19 outcomes. - Enrico Longato; Mario Luca Morieri; Giovanni Sparacino; Barbara Di Camillo; Annamaria Cattelan; Sara Lo Menzo; Marco Trevenzoli; Andrea Vianello; Gabriella Guarnieri; Federico Lionello; Angelo Avogaro; Paola Fioretto; et al. (Comput. Methods Programs Biomed., 2022)

Dealing with Data Scarcity in Rare Diseases: Dynamic Bayesian Networks and Transfer Learning to Develop Prognostic Models of Amyotrophic Lateral Sclerosis. - Enrico Longato; Erica Tavazzi; Adriano Chiò; Gabriele Mora; Giovanni Sparacino; Barbara Di Camillo (AIME, 2023)

Overview of iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge. - Guglielmo Faggioli; Alessandro Guazzo; Stefano Marchesin 001; Laura Menotti; Isotta Trescato; Helena Aidos; Roberto Bergamaschi; Giovanni Birolo; Paola Cavalla; Adriano Chiò; Arianna Dagliati; Mamede de Carvalho; et al. (CLEF (Working Notes), 2023)

Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2023. - Guglielmo Faggioli; Alessandro Guazzo; Stefano Marchesin 001; Laura Menotti; Isotta Trescato; Helena Aidos; Roberto Bergamaschi; Giovanni Birolo; Paola Cavalla; Adriano Chiò; Arianna Dagliati; Mamede de Carvalho; et al. (CLEF, 2023)

Baseline Machine Learning Approaches To Predict Multiple Sclerosis Disease Progression. - Alessandro Guazzo; Isotta Trescato; Enrico Longato; Erica Tavazzi; Martina Vettoretti; Barbara Di Camillo (CLEF (Working Notes), 2023)

DAVI: A Dataset for Automatic Variant Interpretation. - Francesca Longhin; Alessandro Guazzo; Enrico Longato; Nicola Ferro 001; Barbara Di Camillo (CLEF, 2023)

BRAINTEASER ALS and MS Datasets. - Guglielmo Faggioli; Alessandro Guazzo; Stefano Marchesin 001; Laura Menotti; Isotta Trescato; Helena Aidos; Roberto Bergamaschi; Giovanni Birolo; Paola Cavalla; Adriano Chiò; Arianna Dagliati; Mamede de Carvalho; et al. (Zenodo, 2023)

Artificial intelligence and statistical methods for stratification and prediction of progression in amyotrophic lateral sclerosis: A systematic review. - Erica Tavazzi; Enrico Longato; Martina Vettoretti; Helena Aidos; Isotta Trescato; Chiara Roversi; Andreia S. Martins; Eduardo N. Castanho; Ruben Branco; Diogo F. Soares; Alessandro Guazzo; Giovanni Birolo; et al. (Artif. Intell. Medicine, 2023)

iDPP@CLEF 2023 - Participants' repositories for the Intelligent Disease Prediction Progression Challenge. - Guglielmo Faggioli; Alessandro Guazzo; Stefano Marchesin 001; Laura Menotti; Isotta Trescato; Helena Aidos; Roberto Bergamaschi; Giovanni Birolo; Paola Cavalla; Adriano Chiò; Arianna Dagliati; Mamede de Carvalho; et al. (Zenodo, 2023)

Machine Learning Models Highlight the Impact of Pollution and Weather Patterns on Relapse Occurrence in Multiple Sclerosis Patients. - Elena Marinello; Erica Tavazzi; Enrico Longato; Pietro Bosoni; Arianna Dagliati; Mahin Vazifehdan; Riccardo Bellazzi; Isotta Trescato; Alessandro Guazzo; Martina Vettoretti; Eleonora Tavazzi; Lara Ahmad; et al. (BIBM, 2024)

Overview of iDPP@CLEF 2024: The Intelligent Disease Progression Prediction Challenge. - Giovanni Birolo; Pietro Bosoni; Guglielmo Faggioli; Helena Aidos; Roberto Bergamaschi; Paola Cavalla; Adriano Chiò; Arianna Dagliati; Mamede de Carvalho; Giorgio Maria Di Nunzio; Piero Fariselli; Jose Manuel García Dominguez; et al. (CLEF (Working Notes), 2024)

Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2024. - Giovanni Birolo; Pietro Bosoni; Guglielmo Faggioli; Helena Aidos; Roberto Bergamaschi; Paola Cavalla; Adriano Chiò; Arianna Dagliati; Mamede de Carvalho; Giorgio Maria Di Nunzio; Piero Fariselli; Jose Manuel García Dominguez; et al. (CLEF (2), 2024)

Using Wearable and Environmental Data to Improve the Prediction of Amyotrophic Lateral Sclerosis and Multiple Sclerosis Progression: an Explorative Study. - Elena Marinello; Alessandro Guazzo; Enrico Longato; Erica Tavazzi; Isotta Trescato; Martina Vettoretti; Barbara Di Camillo (CLEF (Working Notes), 2024)

Characterization of Chronic Kidney Disease Progression in Patients with Diabetes via Group-Based Multi-Trajectory Modeling. - Alessandro Guazzo; Enrico Longato; Gian Paolo Fadini; Giovanni Sparacino; Rema Padman; Barbara Di Camillo (EMBC, 2024)

Predicting Multiple Sclerosis Worsening Using Stratification-Based and Time-Dependent Variables Extracted from Routine Visits Data. - Alessandro Guazzo; Enrico Longato; Isotta Trescato; Erica Tavazzi; Adriano Chiò; Umberto Manera; Grazia Zocco; Paola Cavalla; Marco Vercellino; Lara Ahmad; Eleonora Tavazzi; Roberto Bergamaschi; et al. (LOD (2), 2024)

Unveiling Trustworthy AI Challenges: Characterizing Prediction Reliability. - Isotta Trescato; Alessandro Guazzo; Enrico Longato; Erica Tavazzi; Martina Vettoretti; Umberto Manera; Adriano Chiò; Marta Gromicho; Inês Alves; Mamede de Carvalho; Barbara Di Camillo (RTSI, 2024)

Exploring the Impact of Environmental Pollutants on Multiple Sclerosis Progression. - Elena Marinello; Erica Tavazzi; Enrico Longato; Pietro Bosoni; Arianna Dagliati; Mahin Vazifehdan; Riccardo Bellazzi; Isotta Trescato; Alessandro Guazzo; Martina Vettoretti; Eleonora Tavazzi; Lara Ahmad; et al. (CoRR, 2024)

Effect of Clinical History on Predictive Model Performance for Renal Complications of Diabetes. - Davide Dei Cas; Barbara Di Camillo; Gian Paolo Fadini; Giovanni Sparacino; Enrico Longato (CoRR, 2024)

BRAINTEASER ALS and MS Datasets. - Guglielmo Faggioli; Stefano Marchesin 001; Laura Menotti; Helena Aidos; Roberto Bergamaschi; Giovanni Birolo; Pietro Bosoni; Paola Cavalla; Adriano Chiò; Arianna Dagliati; Mamede de Carvalho; Giorgio Maria Di Nunzio; et al. (Zenodo, 2024)

DAVI: A Dataset for Automatic Variant Interpretation. - Francesca Longhin; Alessandro Guazzo; Enrico Longato; Nicola Ferro 001; Barbara Di Camillo (Zenodo, 2024)

iDPP@CLEF 2024 - Participants' repositories for the Intelligent Disease Prediction Progression Challenge. - Giovanni Birolo; Pietro Bosoni; Guglielmo Faggioli; Helena Aidos; Roberto Bergamaschi; Paola Cavalla; Adriano Chiò; Arianna Dagliati; Mamede de Carvalho; Giorgio Maria Di Nunzio; Piero Fariselli; Jose Manuel García Dominguez; et al. (Zenodo, 2024)

Predicting clinical events characterizing the progression of amyotrophic lateral sclerosis via machine learning approaches using routine visits data: a feasibility study. - Alessandro Guazzo; Michele Atzeni; Elena Idi; Isotta Trescato; Erica Tavazzi; Enrico Longato; Umberto Manera; Adriano Chiò; Marta Gromicho; Inês Alves; Mamede de Carvalho; Martina Vettoretti; et al. (BMC Medical Informatics Decis. Mak., 2024)

Exploring the Use of Projecting Conflicting Gradients in Multi-task Neural Networks with an Application to Amyotrophic Lateral Sclerosis. - Davide Dei Cas; Enrico Longato; Erica Tavazzi; Umberto Manera; Adriano Chiò; Marta Gromicho; Inês Alves; Mamede de Carvalho; Barbara Di Camillo (AIME (1), 2025)

The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes. - Davide Dei Cas; Barbara Di Camillo; Gian Paolo Fadini; Giovanni Sparacino; Enrico Longato (Comput. Methods Programs Biomed., 2025)

BRAINTEASER ALS and MS Datasets. - Guglielmo Faggioli; Stefano Marchesin 001; Laura Menotti; Helena Aidos; Roberto Bergamaschi; Giovanni Birolo; Pietro Bosoni; Paola Cavalla; Adriano Chiò; Arianna Dagliati; Mamede de Carvalho; Giorgio Maria Di Nunzio; et al. (Zenodo, 2025)