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Sara C. Madeira

Distinguished Publications @ LASIGE Workshop 2026
Generating realistic synthetic patients with deep learning to advance healthcare research
Diogo F. Soares and Sara C. Madeira publish Pattern Recognition Journal
Miguel G. Silva and Sara C. Madeira research published in Pattern Recognition journal
LASIGE's 2024 PhD graduations
LASIGE researcher published in Biefings in Bioinformatics
LASIGE's paper published in Nature Communications
Miguel G. Silva and Sara C. Madeira research published in ACM Computing Surveys
Helena Aidos and Sara C. Madeira's work published in Translational Neurodegeneration journal
LASIGE researchers Diogo F. Soares and Sara C. Madeira publish at Pattern Recognition
LASIGE research published at BMC Bioinformatics
LASIGE research published in Environment and Planning B: Urban Analytics and City Science
Sara C. Madeira distinguished with Ciências 2022 Research Award
LASIGE team co-authors research published in Artificial Intelligence in Medicine journal
LASIGE's paper published in Scientific Reports 
Andreia Sofia Teixeira at CompleNet's Organising Committee
8th LASIGE Workshop (2023)
BRAINTEASER Mid-term Workshop
LASIGE published in the Journal of Biomedical Informatics
LASIGE at INForum 2022 organization
LASIGE's research published in BMC Bioinformatics
Sara C. Madeira awarded at the ULisboa/CGD Scientific Prize Ceremony
LASIGE publishes @ Water journal
Sara C. Madeira won "Computer Sciences and Informatic Engineering-2021 prize" by ULisboa/CGD
LASIGE co-organizer of Challenge iDPP@CLEF 2022
Sara C. Madeira distinguished with Computer Sciences and Informatic Engineering-2019/20 prize by ULisboa/CGD
6th LASIGE Workshop (2021)
Andreia Martins and Sara Madeira publish in IEEE/ACM Transactions on Computational Biology and Bioinformatics
Sara Madeira’s work on ALS published in Journal of Biomedical Informatics
Sara C. Madeira published in Pattern Recognition
Sara C. Madeira's paper published at IEEE Transactions on Intelligent Transportation Systems
Brainteasear kick-off meeting, an H2020 project
João Lobo and Sara C. Madeira's paper published at BMC Bioinformatics
LASIGE projects selected by FCT at the Call 2020
LASIGE gets H2020 funding in Artificial Intelligence by BRAINSTEASER project
Sara C. Madeira talk @ ESCI-2019
Sara C. Madeira project manager of Lisbon Urban Data Laboratory

ONGOING

Acronym Title Funding Entity Start Date End Date
DETECT2AD Two Alzheimer’s - Diagnosing distinct types of Alzheimer’s disease in CSF and plasma COMPETE20230 EU FCT P2030 15/07/2025 13/07/2028
TRACKD learning Temporal pRogression pAtterns for Chronic Kidney Disease prognosis FCT | LASIGE 01/10/2026 31/12/2027
ParkProfile Temporal Multimodal PD Patients Profiling FCT | LASIGE 01/12/2025 30/09/2026

PAST

Acronym Title Funding Entity Start Date End Date
BRAINTEASER BRinging Artificial INTelligencE home for a better cAre of amyotrophic lateral sclerosis and multiple SclERosis EU H2020 01/01/2021 30/06/2025
AIpALS Advanced LearnIng Models using Patient Profiles and Disease Progression Patterns for Prognostic Prediction in ALS FCT 01/03/2021 28/02/2025
CIRCLES Controlling mIcRobiomes CircuLations for bEtter food Systems EU H2020 01/11/2018 31/10/2024
LAIfeBlood Artificial Intelligence for Blood Management FCT 01/01/2020 31/12/2023
iCare4U Decision support system for personalized medicine in ICUs FCT 01/06/2018 31/05/2022
PREDICT Personalized therapy for RhEumatic DIseases via machine learning FCT 01/01/2019 31/12/2021
NEUROCLINOMICS2 Unravelling Prognostic Markers in NEUROdegenerative diseases through CLINical and OMICS data integration FCT 01/07/2016 31/03/2020
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Guglielmo Faggioli, Laura Menotti, Stefano Marchesin, Isotta Trescato, Lara Ahmad, Helena Aidos, Anca Loredana Alungulese, Riccardo Bellazzi, Roberto Bergamaschi, Giovanni Birolo, Pietro Bosoni, Maria Fernanda Cabrera-Umpiérrez, Paola Cavalla, Adriano Chió, Arianna Dagliati, Mamede de Carvalho, Piero Fariselli, José Manuel García Dominguez, Sergio González Martínez, Marta Gromicho, Alessandro Guazzo, Aleksandar Jovanović, Borko Kostić, Enrico Longato, Sara C. Madeira, Umberto Manera, José Luis Muñoz Blanco, Eleonora Tavazzi, Erica Tavazzi, Elena Trasobares Iglesias, Vladimir Urošević, Martina Vettoretti, Giorgio Maria Di Nunzio, Gianmaria Silvello, Barbara Di Camillo, Nicola Ferro. The BRAINTEASER Datasets: Clinical, Wearable and Environmental Data for ALS & MS Progression Modeling. Scientific Data, 12, Springer Science and Business Media LLC, 2025 [Biblios]
André Esteves, Sara C. Madeira, Helena Aidos. Temporal Phenotyping of ALS Patients using Machine Learning. Master's dissertation, 2025 [Biblios]
Miguel G. Silva, Sara C. Madeira, Rui Henriques. Cutting through the noise: Explaining residuals in multivariate time series with motif analysis. Pattern Recognition, 169, Elsevier BV, 2025 [Biblios]
Diogo F. Soares, Rui Henriques, Sara C. Madeira. TriHSPAM: Triclustering heterogeneous longitudinal clinical data using sequential patterns. Pattern Recognition, 167, Elsevier BV, 2025 [Biblios]
André Filipe Correia Gomes, Mário A. T. Figueiredo, Sara C. Madeira. Advances in Partial Information Decomposition. PhD thesis, 2025 [Biblios]
Dias, André Teixeira, Tomás, Helena Isabel Aidos Lopes, Madeira, Sara Alexandra Cordeiro. Triclustering-based patient stratification : a case study in Multiple and Amyotrophic Lateral Sclerosis. Master's dissertation, 2025 [Biblios]
Oliveira, Joel Pereira de, Tomás, Helena Isabel Aidos Lopes , Madeira, Sara . Predicting Clinically Relevant Endpoints in ALS using Multi-label Classification. Master's dissertation, 2025 [Biblios]
Carvalho, Leonor Pedro, Aidos, Helena, Madeira, Sara. Data-driven stratification of ALS patients using phrenic nerve signals. Master's dissertation, 2025 [Biblios]
Miguel Pego Roque, Andreia S. Martins, Marta Gromicho, Mamede de Carvalho, Sara C. Madeira, Pedro Tomás , Helena Aidos. Deep Temporal Consensus Clustering for Patient Stratification in Amyotrophic Lateral Sclerosis. In European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2024). i6doc.com, 2024 [Biblios]
Chiara Solito, Manuele Bicego, Ferdinando Cicalese, Sara C. Madeira. A Random Forest approach to biclustering. Master's dissertation, 2024 [Biblios]
Andreia S. Martins, Daniela M. Amaral, Eduardo N. Castanho, Diogo F. Soares, Ruben Branco, Sara C. Madeira, Helena Aidos. Predicting the functional rating scale and self-assessment status of ALS patients with sensor data. In Intelligent Disease Progression Prediction (iDPP) at CLEF 2024, pages 1366-1379. CEUR-WS.org, 2024 [Biblios]
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, Marta Gromicho, Alessandro Guazzo, Enrico Longato, Sara C. Madeira, Umberto Manera, Stefano Marchesin, Laura Menotti, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Isotta Trescato, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro. Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2024. In Experimental IR Meets Multilinguality, Multimodality, and Interaction (CLEF 2024), pages 118-139. Springer Nature Switzerland, 2024 [Biblios]
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, Marta Gromicho, Alessandro Guazzo, Enrico Longato, Sara C. Madeira, Umberto Manera, Stefano Marchesin, Laura Menotti, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Isotta Trescato, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro. Overview of iDPP@CLEF 2024: The Intelligent Disease Progression Prediction Challenge. In Intelligent Disease Progression Prediction (iDPP) at CLEF 2024, pages 1312-1330(3740). CEUR-WS.org, 2024 [Biblios]
Eduardo Castanho, Helena Aidos, Sara C. Madeira. Biclustering Data Analysis: A Comprehensive Survey. Briefings in Bioinformatics, 25(4), Oxford University Press (OUP), 2024 [Biblios]
Daniela M. Amaral, Diogo F. Soares, Marta Gromicho, Mamede de Carvalho, Sara C. Madeira, Pedro Tomás, Helena Aidos. Temporal stratification of amyotrophic lateral sclerosis patients using disease progression patterns. Nature Communications, 15(5717), Springer Science and Business Media LLC, 2024 [Biblios]
Miguel G. Silva, Sara C. Madeira, Rui Henriques. A Comprehensive Survey on Biclustering-based Collaborative Filtering. ACM Computing Surveys, Association for Computing Machinery (ACM), 2024 [Biblios]
Eduardo N Castanho, Helena Aidos, Sara C Madeira. Biclustering data analysis: a comprehensive survey, Briefings in Bioinformatics, 2024 [Biblios]
Daniela Moutinho, Vera M. Mendes, Alessandro Caula, Sara C. Madeira, Inês Baldeiras, Manuela Guerreiro, Sandra Cardoso, Johan Gobom, Henrik Zetterberg, Isabel Santana, Alexandre De Mendonça, Helena Aidos, Bruno Manadas. Pathophysiological subtypes of mild cognitive impairment due to Alzheimer’s disease identified by CSF proteomics. Translational Neurodegeneration, 13(1), Springer Science and Business Media LLC, 2024 [Biblios]
Helena Aidos, Roberto Bergamaschi, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Barbara Di Camillo, Mamede Alves de Carvalho, Nicola Ferro, Piero Fariselli, Jose Manuel García Dominguez, Sara C. Madeira, Eleonora Tavazzi. iDPP@CLEF 2024: The Intelligent Disease Progression Prediction Challenge. In 46th European Conference on Information Retrieval (ECIR 2024), pages 53-59. Springer Nature Switzerland, 2024 [Biblios]
Diogo F. Soares, Rui Henriques, Sara C. Madeira. Comprehensive assessment of triclustering algorithms for three-way temporal data analysis. Pattern Recognition, 150, Elsevier BV, 2024 [Biblios]
Seguro, Afonso Manuel Tito Lopes, Tomás, Helena Isabel Aidos Lopes, Madeira, Sara Alexandra Cordeiro. Temporal unsupervised learning models to study ALS progression. Master's dissertation, 2024 [Biblios]
Diogo Filipe Marques Soares, Sara Alexandra Cordeiro Madeira, Rui Miguel Carrasqueiro Henriques. Triclustering three-way temporal and heterogeneous data : targeting predictive and descriptive tasks for biomedical applications. PhD thesis, 2024 [Biblios]
Eduardo N. Castanho, João P. Lobo, Rui Henriques, Sara C. Madeira. G-bic: generating synthetic benchmarks for biclustering. BMC Bioinformatics, 24(1), Springer Science and Business Media LLC, 2023 [Biblios]
Miguel G Silva, Sara C Madeira, Rui Henriques. Actionable descriptors of spatiotemporal urban dynamics from large-scale mobile data: A case study in Lisbon city. Environment and Planning B: Urban Analytics and City Science, SAGE Publications, 2023 [Biblios]
Ruben Branco, Joana Barros Valente, Andreia S. Martins, Diogo F. Soares, Eduardo N. Castanho, Sara C. Madeira, Helena Aidos. Survival analysis for multiple sclerosis: predicting risk of disease worsening. In Intelligent Disease Progression Prediction (iDPP) at CLEF 2023 , pages 1199-1209. CEUR-WS.org , 2023 [Biblios]
Ruben Branco, Diogo F. Soares, Andreia S. Martins, Joana Barros Valente, Eduardo N. Castanho, Sara C. Madeira, Helena Aidos. Investigating the Impact of Environmental Data on ALS Prognosis with Survival Analysis. In Intelligent Disease Progression Prediction (iDPP) at CLEF 2023, pages 1186-1198. CEUR-WS.org, 2023 [Biblios]
Marco André Gonçalves Pinheiro, Sara C. Madeira, Alexandre P. Francisco . SHORT-TERM ELECTRIC LOAD FORECASTING. PhD thesis, 2023 [Biblios]
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, Daniele Pala, Pietro Bosoni, Adriano Chiò, Umberto Manera, Mamede de Carvalho, Bruno Miranda, Marta Gromicho, Inês Alves, Riccardo Bellazzi, Arianna Dagliati, Piero Fariselli, Sara C. Madeira, Barbara Di Camillo. Artificial intelligence and statistical methods for stratification and prediction of progression in amyotrophic lateral sclerosis: A systematic review. Artificial Intelligence in Medicine, Elsevier BV, 2023 [Biblios]
Diogo F. Soares, Rui Henriques, Marta Gromicho, Mamede de Carvalho, Sara C. Madeira. Triclustering-based classification of longitudinal data for prognostic prediction: targeting relevant clinical endpoints in amyotrophic lateral sclerosis. Scientific Reports, 13(1), Springer Science and Business Media LLC, 2023 [Biblios]
Marco G. Pinheiro, Sara C. Madeira, Alexandre P. Francisco. Short-term electricity load forecasting—A systematic approach from system level to secondary substations. Applied Energy, 332, Elsevier BV, 2023 [Biblios]
Helena Aidos, Roberto Bergamaschi, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Barbara Di Camillo, Mamede Alves de Carvalho, Nicola Ferro, Piero Fariselli, Jose Manuel García Dominguez, Sara C. Madeira, Eleonora Tavazzi. iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge. In European Conference on Information Retrieval, pages 491-498. Springer Nature Switzerland, 2023 [Biblios]
Valente, Joana Filipa Barros, Tomás, Helena Isabel Aidos Lopes, Madeira, Sara Alexandra Cordeiro. Relapse Prediction in Multiple Sclerosis: a Supervised Learning Approach. Master's dissertation, 2023 [Biblios]
Silva, Lucas Barreto, Madeira, Sara Alexandra Cordeiro, Garcia, Nuno Ricardo da Cruz. Deep Learning for predicting disease progression of clinical endpoints in ALS. Master's dissertation, 2023 [Biblios]
Garcia, Afonso Neves, Madeira, Sara Alexandra Cordeiro, Aidos, Helena. Modelo preditivo para a aquisição do produto Solar da EDP Comercial. Master's dissertation, 2023 [Biblios]
Guglielmo Faggioli, Alessandro Guazzo, Stefano Marchesin, Laura Menotti, Isotta Trescato, Helena Aidos, Roberto Bergamaschi, Giovanni Birolo, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Mamede de Carvalho, Giorgio Maria Di Nunzio, Piero Fariselli, Jose Manuel García Dominguez, Marta Gromicho, Enrico Longato, Sara C. Madeira, Umberto Manera, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro. Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2023. In 14th International Conference of the CLEF Association, CLEF 2023, pages 343-369. Springer Nature Switzerland, 2023 [Biblios]
Guglielmo Faggioli, Alessandro Guazzo, Stefano Marchesin, Laura Menotti, Isotta Trescato, Helena Aidos, Roberto Bergamaschi, Giovanni Birolo, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Mamede de Carvalho, Giorgio Maria Di Nunzio, Piero Fariselli, Jose Manuel García Dominguez, Marta Gromicho, Enrico Longato, Sara C. Madeira, Umberto Manera, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro. Overview of iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge. In Intelligent Disease Progression Prediction (iDPP) at CLEF. CEUR-WS.org, 2023 [Biblios]
Diogo F. Soares, Rui Henriques, Marta Gromicho, Mamede de Carvalho, Sara C. Madeira. Learning prognostic models using a mixture of biclustering and triclustering: Predicting the need for non-invasive ventilation in Amyotrophic Lateral Sclerosis. Journal of Biomedical Informatics, 134, Elsevier BV, 2022 [Biblios]
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, Sara C. Madeira, Mamede de Carvalho, Marta Gromicho, Adriano Chiò, Umberto Manera, Arianna Dagliati, Giovanni Birolo, Helena Aidos, Barbara Di Camillo, Nicola Ferro. Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2022. In 12th International Conference of the CLEF Association, CLEF 2022, pages 395-422. Springer International Publishing, 2022 [Biblios]
Alessandro Guazzo, Isotta Trescato, Enrico Longato, Enidia Hazizaj, Dennis Dosso, Guglielmo Faggioli, Giorgio Maria Di Nunzio, Gianmaria Silvello, Martina Vettoretti, Erica Tavazzi, Chiara Roversi, Pietro Fariselli, Sara C. Madeira, Mamede de Carvalho, Marta Gromicho, Adriano Chiò, Umberto Manera, Arianna Dagliati, Giovanni Birolo, Helena Aidos, Barbara Di Camillo, Nicola Ferro. Overview of iDPP@CLEF 2022: The Intelligent Disease Progression Prediction Challenge. In Intelligent Disease Progression Prediction (iDPP) at CLEF, pages 1130-1210. CEUR-WS.org, 2022 [Biblios]
Ruben Branco, Diogo F. Soares, Andreia S. Martins, Eleonora Auletta, Eduardo N. Castanho, Susana Nunes, Filipa Serrano, Rita T. Sousa, Catia Pesquita, Sara C. Madeira, Helena Aidos. Hierarchical Modelling for ALS Prognosis: Predicting the Progression Towards Critical Events. In Intelligent Disease Progression Prediction (iDPP) at CLEF, pages 1211-1227. CEUR-WS.org, 2022 [Biblios]
Susana Nunes, Rita T. Sousa, Filipa Serrano, Ruben Branco, Diogo F. Soares, Andreia S. Martins, Eleonora Auletta, Eduardo N. Castanho, Sara C. Madeira, Helena Aidos,  Catia Pesquita. Explaining Artificial Intelligence Predictions of Disease Progression with Semantic Similarity. In Intelligent Disease Progression Prediction (iDPP) at CLEF 2022. CEUR-WS.org, 2022 [Biblios]
Maria Lua Nunes, Duarte Folgado, Carlos Fujao, Luis Silva, Joao Rodrigues, Pedro Matias, Marilia Barandas, Andre V. Carreiro, Sara Madeira, Hugo Gamboa. Posture Risk Assessment in an Automotive Assembly Line Using Inertial Sensors. IEEE Access, 10, Institute of Electrical and Electronics Engineers (IEEE), 2022 [Biblios]
Marta D.M. Noronha, Rui Henriques, Sara C. Madeira, Luis E. Zárate. Impact of metrics on biclustering solution and quality: A review. Pattern Recognition, 127, Elsevier BV, 2022 [Biblios]
Miguel G. Silva, Sara C. Madeira, Rui Henriques. Water Consumption Pattern Analysis Using Biclustering: When, Why and How. Water, 14(12), MDPI AG, 2022 [Biblios]
Marco G. Pinheiro, Sara C. Madeira, Alexandre P. Francisco. Shapelets to Classify Energy Demand Time Series. Energies, 15(8), MDPI AG, 2022 [Biblios]
Marta Gromicho, Tiago Leão, Miguel Oliveira Santos, Susana Pinto, Alexandra M. Carvalho, Sara C. Madeira, Mamede de Carvalho. Dynamic Bayesian Networks for stratification of disease progression in Amyotrophic Lateral Sclerosis. European Journal of Neurology, Wiley, 2022 [Biblios]
Pedro Miguel Pereira Domingues, Sara C. Madeira, Nuno Ricardo da Cruz Garcia . Prognostic prediction models using Self-Attention for ICU patients developing acute kidney injury. Master's dissertation, 2022 [Biblios]
Pedro Giesteira Cotovio, Sara C. Madeira, André V. Carreiro. Towards reinforcement learning based N­Clustering. Master's dissertation, 2022 [Biblios]
João Miguel Ferreira Castanheira, Sara C. Madeira, Pedro T. G. Monteiro. Characterization of Behavioural Patterns of Portuguese Blood Donors using Supervised and Unsupervised Learning. Master's dissertation, 2022 [Biblios]
Alessandro Caula, Sara C. Madeira, Helena Aidos, Pietro Di Lena. Identifying subtypes of Mild Cognitive Impairment due to Alzheimer’s disease in cerebrospinal fluid proteomics: a Machine Learning approach. Master's dissertation, 2022 [Biblios]
Costa, Mariana Lourenço, Madeira, Sara Alexandra Cordeiro, Garcia, Nuno Ricardo da Cruz. Plataforma de apoio a utentes e profissionais de desporto e nutrição. Master's dissertation, 2022 [Biblios]
Dias, António Antunes, Madeira, Sara Alexandra Cordeiro, Matute, Israel. Better Science Through an Enhanced User Interface with the ALMA Archive. Master's dissertation, 2022 [Biblios]
Óscar San José Rodríguez, Sara C. Madeira, Giulia Babbi, Pier Luigi Martelli. Toolkit for differential analysis of microbiome data. Master's dissertation, 2022 [Biblios]
Maria Lua de Coelho Nunes, Sara C. Madeira, André Carreiro . Quantifying the ergonomic risk and biomechanical exposure in automotive assembly lines. Master's dissertation, 2021 [Biblios]
Francisco Lopes, Sara C. Madeira, Pedro Monteiro. Unravelling Patterns from a Blood Donation Data Set using Machine Learning Approaches. Master's dissertation, 2021 [Biblios]
Eleonora Auletta, Sara C. Madeira, Cláudia Antunes. Data-Driven Approaches for ALS Patient Stratification using Clinical Profiles. Master's dissertation, 2021 [Biblios]
Andreia Sofia Santos Martins, Sara C. Madeira. Learning models using disease progression patterns for prognostic prediction in ALS. Master's dissertation, 2021 [Biblios]
Marcel Müller, Marta Gromicho, Mamede de Carvalho, Sara C. Madeira. Explainable Models of Disease Progression in ALS: Learning from Longitudinal Clinical Data with Recurrent Neural Networks and Deep Model Explanation. Computer Methods and Programs in Biomedicine Update, Elsevier BV, 2021 [Biblios]
Andreia S. Martins, Marta Gromicho, Susana Pinto, Mamede de Carvalho, Sara C. Madeira. Learning Prognostic Models using Disease Progression Patterns: Predicting the Need for Non-Invasive Ventilation in Amyotrophic Lateral Sclerosis. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 1-1, Institute of Electrical and Electronics Engineers (IEEE), 2021 [Biblios]
Tiago Leão, Sara C. Madeira, Marta Gromicho, Mamede de Carvalho, Alexandra M. Carvalho. Learning dynamic Bayesian networks from time-dependent and time-independent data: Unraveling disease progression in Amyotrophic Lateral Sclerosis. Journal of Biomedical Informatics, 117, Elsevier BV, 2021 [Biblios]
Adriano António Pinheiro Mão de Ferro, Pedro Miguel Frazão Fernandes Ferreira, Sara Alexandra Cordeiro Madeira. Aprendizagem automática para classificar a cobertura do solo em espaços verdes urbanos através de dados de satélite. Master's dissertation, 2021 [Biblios]
Francisco Neves, Anna C. Finamore, Sara C. Madeira, Rui Henriques. Mining Actionable Patterns of Road Mobility From Heterogeneous Traffic Data Using Biclustering. IEEE Transactions on Intelligent Transportation Systems, 1-16, Institute of Electrical and Electronics Engineers (IEEE), 2021 [Biblios]
Rui Henriques, Sara C. Madeira. FleBiC: Learning classifiers from high-dimensional biomedical data using discriminative biclusters with non-constant patterns. Pattern Recognition, Elsevier BV, 2021 [Biblios]
João Lobo, Rui Henriques, Sara C. Madeira. G-Tric: generating three-way synthetic datasets with triclustering solutions. BMC Bioinformatics, 22(1), Springer Science and Business Media LLC, 2021 [Biblios]
André Ferreira, Sara C. Madeira, Marta Gromicho, Mamede de Carvalho, Susana Vinga, Alexandra M. Carvalho. Predictive Medicine Using Interpretable Recurrent Neural Networks. In Pattern Recognition. ICPR International Workshops and Challenges,Lecture Notes in Computer Science, pages 187-202. Springer International Publishing, 2021 [Biblios]
Tiago Leão, Sara C. Madeira, Alexandra Carvalho. Profiling ALS disease progression through data mining techniques. Master's dissertation, 2020 [Biblios]
Diogo Soares, Rui Henriques, Marta Gromicho, Susana Pinto, Mamede de Carvalho, Sara C. Madeira. Towards Triclustering-Based Classification of Three-Way Clinical Data: A Case Study on Predicting Non-invasive Ventilation in ALS. In Advances in Intelligent Systems and Computing,Practical Applications of Computational Biology & Bioinformatics, 14th International Conference (PACBB 2020), pages 112-122. Springer International Publishing, 2020 [Biblios]
Marta Gromicho, Manuel Figueiral, Hilmi Uysal, Julian Grosskreutz, Magdalena Kuzma-Kozakiewicz, Susana Pinto, Susanne Petri, Sara C. Madeira, Michael Swash, Mamede Carvalho. Spreading in ALS: The relative impact of upper and lower motor neuron involvement. Annals of Clinical and Translational Neurology, 7(7):1181-1192, Wiley, 2020 [Biblios]
Telma Pereira, Sandra Cardoso, Manuela Guerreiro, Alexandre Mendonça, Sara C. Madeira. Targeting the uncertainty of predictions at patient-level using an ensemble of classifiers coupled with calibration methods, Venn-ABERS, and Conformal Predictors: A case study in AD. Journal of Biomedical Informatics, 101, Elsevier BV, 2020 [Biblios]
Diogo Filipe Marques Soares, Sara Alexandra Cordeiro Madeira. Learning Predictive Models From Temporal Three-way Data Using Triclustering: Applications in Clinical Data Analysis. Master's dissertation, 2020 [Biblios]
Patrícia Andreia Alves Falcão, Sara Madeira, Nuno André da Silva. Predicting post-surgical length of stay using machine learning. Master's dissertation, 2020 [Biblios]
Miguel Miranda Garção da Silva, Sara Alexandra Cordeiro Madeira. User-Specific Bicluster-based collaborative Filtering. Master's dissertation, 2020 [Biblios]
João Pedro Pereira Lobo, Sara Alexandra Cordeiro Madeira. G-Tric: enhancing triclustering evaluation using three-way synthetic datasets with ground truth. Master's dissertation, 2020 [Biblios]
Eduardo Jorge do Nascimento Rolha Castanho, Sara Alexandra Cordeiro. Biclustering FMRI Time Series. Master's dissertation, 2020 [Biblios]
Ana Catarina Domingos Pelicano, Raquel Conceição, Sara Madeira. Modelling the head and neck region for microwave imaging of cervical lymph nodes. Master's dissertation, 2020 [Biblios]
Joana Matos, Sofia Pires, Helena Aidos, Marta Gromicho, Susana Pinto, Mamede de Carvalho, Sara C. Madeira. Unravelling Disease Presentation Patterns in ALS Using Biclustering for Discriminative Meta-Features Discovery. In Bioinformatics and Biomedical Engineering,Lecture Notes in Computer Science, pages 517-528. Springer International Publishing, 2020 [Biblios]
Sofia Pires, Marta Gromicho, Susana Pinto, Mamede de Carvalho, Sara C. Madeira. Patient Stratification Using Clinical and Patient Profiles: Targeting Personalized Prognostic Prediction in ALS. In Bioinformatics and Biomedical Engineering,Lecture Notes in Computer Science, pages 529-541. Springer International Publishing, 2020 [Biblios]
Telma Pereira, Sofia Pires, Marta Gromicho, Mamede de Carvalho, Sara C. Madeira. Predicting assisted ventilation in Amyotrophic Lateral Sclerosis using a mixture of experts and conformal predictors. In KDD 2019 Workshop on Applied Data Science for Healthcare, 2019 [Biblios]
Telma Pereira, Sara C. Madeira, Manuela Guerreiro. Prognostic models targeting time to conversion, stable predictors, and reliability at patient-level: Predicting progression from mild cognitive impairment to dementia. PhD thesis, 2019 [Biblios]
Joao M.C. Sousa, Susana M. Vieira, Joao P. Carvalho, Sara C. Madeira, Leo Celi, Stan N. Finkelstein. An Architecture Based on Fuzzy Systems for Personalized Medicine in ICUs. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2019 [Biblios]
Teixeira, David Carriço, Pesquita, Cátia, Madeira, Sara Alexandra Cordeiro. Understanding ALS patients using semantic similarity. Master's dissertation, 2019 [Biblios]
Joana Sofia Santos de Matos, Madeira, Sara Alexandra Cordeiro. Biclustering electronic health records to unravel disease presentation patterns. Master's dissertation, 2019 [Biblios]
Telma Pereira, Francisco L. Ferreira, Sandra Cardoso, Dina Silva, Alexandre de Mendonça, Manuela Guerreiro, Sara C. Madeira. Neuropsychological predictors of conversion from mild cognitive impairment to Alzheimer’s disease: a feature selection ensemble combining stability and predictability. BMC Medical Informatics and Decision Making, 18(1), Springer Nature, 2018 [Biblios]
Sofia Isabel Ferro Pires, Sara Alexandra Cordeiro Madeira. A supervised learning approach for prognostic prediction in ALS using disease progression groups and patient profiles. Master's dissertation, 2018 [Biblios]
Sofia Pires, Marta Gromicho, Susana Pinto, Mamede Carvalho, Sara C. Madeira. Predicting Non-invasive Ventilation in ALS Patients Using Stratified Disease Progression Groups. In 2018 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2018 [Biblios]
Rui Henriques, Sara C. Madeira. Triclustering Algorithms for Three-Dimensional Data Analysis: A Comprehensive Survey. ACM Computing Surveys, 51(5):1-43, Association for Computing Machinery (ACM), 2018 [Biblios]
Telma Pereira, Sandra Cardoso, Dina Silva, Manuela Guerreiro, Alexandre de Mendonça, Sara C. Madeira. Ensemble learning with Conformal Predictors: Targeting credible predictions of conversion from Mild Cognitive Impairment to Alzheimer's Disease. In KDD Workshop on Machine Learning for Medicine and Healthcare, 2018 [Biblios]
T Pereira, F Ferreira, M Guerreiro, A Mendonca, Sara C. Madeira. Towards a reliable prediction of conversion from Mild Cognitive Impairment to Alzheimer’s Disease: stepwise learning using time windows. In Proceedings of The First Workshop Medical Informatics and Healthcare held with the 23rd SIGKDD Conference on Knowledge Discovery and Data Mining, pages 19-26(69). Proceedings of Machine Learning Research (PMLR), 2017 [Biblios]
Telma Pereira, Luís Lemos, Sandra Cardoso, Dina Silva, Ana Rodrigues, Isabel Santana, Alexandre de Mendonça, Manuela Guerreiro, Sara C. Madeira. Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows. BMC Medical Informatics and Decision Making, 17(1), Springer Nature, 2017 [Biblios]
Rui Henriques, Sara C. Madeira. BSig: evaluating the statistical significance of biclustering solutions. Data Mining and Knowledge Discovery, 32(1):124-161, Springer Nature, 2017 [Biblios]
Rui Henriques, Francisco L. Ferreira, Sara C. Madeira. BicPAMS: software for biological data analysis with pattern-based biclustering. BMC Bioinformatics, 18(1), Springer Nature, 2017 [Biblios]
Francisco L. Ferreira, Sandra Cardoso, Dina Silva, Manuela Guerreiro, Alexandre de Mendonça, Sara C. Madeira. Improving Prognostic Prediction from Mild Cognitive Impairment to Alzheimer’s Disease Using Genetic Algorithms, In Advances in Intelligent Systems and Computing,11th International Conference on Practical Applications of Computational Biology & Bioinformatics, pages 180 - 188. Springer International Publishing, 2017 [Biblios]
Telma Pereira, Sandra Cardoso, Dina Silva, Alexandre de Mendonça, Manuela Guerreiro, Sara C. Madeira. Towards Trustworthy Predictions of Conversion from Mild Cognitive Impairment to Dementia: A Conformal Prediction Approach, In Advances in Intelligent Systems and Computing,11th International Conference on Practical Applications of Computational Biology & Bioinformatics, pages 155 - 163. Springer International Publishing, 2017 [Biblios]