Predicting Non-invasive Ventilation in ALS Patients Using Stratified Disease Progression Groups. - Sofia Pires; Marta Gromicho; Susana Pinto; Mamede de Carvalho; Sara C. Madeira (ICDM Workshops, 2018)

Predicting assisted ventilation in Amyotrophic Lateral Sclerosis using a mixture of experts and conformal predictors. - Telma Pereira; Sofia Pires; Marta Gromicho; Susana Pinto; Mamede de Carvalho; Sara C. Madeira (CoRR, 2019)

Predictive Medicine Using Interpretable Recurrent Neural Networks. - André Ferreira; Sara C. Madeira; Marta Gromicho; Mamede de Carvalho; Susana Vinga; Alexandra M. Carvalho (ICPR Workshops (1), 2020)

Unravelling Disease Presentation Patterns in ALS Using Biclustering for Discriminative Meta-Features Discovery. - Joana Matos; Sofia Pires; Helena Aidos; Marta Gromicho; Susana Pinto; Mamede de Carvalho; Sara C. Madeira (IWBBIO, 2020)

Patient Stratification Using Clinical and Patient Profiles: Targeting Personalized Prognostic Prediction in ALS. - Sofia Pires; Marta Gromicho; Susana Pinto; Mamede de Carvalho; Sara C. Madeira (IWBBIO, 2020)

Towards Triclustering-Based Classification of Three-Way Clinical Data: A Case Study on Predicting Non-invasive Ventilation in ALS. - Diogo F. Soares; Rui Henriques; Marta Gromicho; Susana Pinto; Mamede de Carvalho; Sara C. Madeira (PACBB, 2020)

Learning dynamic Bayesian networks from time-dependent and time-independent data: Unraveling disease progression in Amyotrophic Lateral Sclerosis. - Tiago Leão; Sara C. Madeira; Marta Gromicho; Mamede de Carvalho; Alexandra M. Carvalho (J. Biomed. 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)

Learning prognostic models using a mixture of biclustering and triclustering: Predicting the need for non-invasive ventilation in Amyotrophic Lateral Sclerosis. - Diogo F. Soares; Rui Henriques; Marta Gromicho; Mamede de Carvalho; Sara C. Madeira (J. Biomed. Informatics, 2022)

Learning Prognostic Models Using Disease Progression Patterns: Predicting the Need for Non-Invasive Ventilation in Amyotrophic Lateral Sclerosis. - Andreia S. Martins; Marta Gromicho; Susana Pinto; Mamede de Carvalho; Sara C. Madeira (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

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)

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)

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)

Deep Temporal Consensus Clustering for Patient Stratification in Amyotrophic Lateral Sclerosis. - Miguel Pego Roque; Andreia S. Martins; Marta Gromicho; Mamede de Carvalho; Sara C. Madeira; Pedro Tomás; Helena Aidos (ESANN, 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)

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)

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)

An extensible and unifying approach to retrospective clinical data modeling: the BrainTeaser Ontology. - Guglielmo Faggioli; Laura Menotti; Stefano Marchesin 001; Adriano Chiò; Arianna Dagliati; Mamede de Carvalho; Marta Gromicho; Umberto Manera; Eleonora Tavazzi; Giorgio Maria Di Nunzio; Gianmaria Silvello; Nicola Ferro 001 (J. Biomed. Semant., 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)

Effect of Environmental Personal Exposure on Amyotrophic Lateral Sclerosis Disease Progression. - Pietro Bosoni; Irene Aiello; Umberto Manera; Marta Gromicho; Inês Alves; Barbara Di Camillo; Mamede de Carvalho; Adriano Chiò; Riccardo Bellazzi; Arianna Dagliati (ICHI, 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)