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Sara C. Madeira

Sara Cordeiro Madeira

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affiliation: University of Lisbon, Instituto Superior Técnico, Portugal

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2024
[j42]
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Eduardo N. Castanho, Helena Aidos, Sara C. Madeira:
Biclustering data analysis: a comprehensive survey. Briefings Bioinform. 25(4) (2024)
[j41]
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Eduardo N. Castanho, João Lobo, Rui Henriques, Sara C. Madeira:
Correction: G-bic: generating synthetic benchmarks for biclustering. BMC Bioinform. 25(1): 16 (2024)
[j40]
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Diogo F. Soares, Rui Henriques, Sara C. Madeira:
Comprehensive assessment of triclustering algorithms for three-way temporal data analysis. Pattern Recognit. 150: 110303 (2024)
2023
[j39]
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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. Artif. Intell. Medicine 142: 102588 (2023)
[j38]
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Eduardo N. Castanho, João Lobo, Rui Henriques, Sara C. Madeira:
G-bic: generating synthetic benchmarks for biclustering. BMC Bioinform. 24(1): 457 (2023)
2022
[j37]
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Maria Lua Nunes, Duarte Folgado, Carlos Fujão, Luís Silva, João Rodrigues, Pedro Matias, Marília Barandas, André V. Carreiro, Sara C. Madeira, Hugo Gamboa:
Posture Risk Assessment in an Automotive Assembly Line Using Inertial Sensors. IEEE Access 10: 83221-83235 (2022)
[j36]
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Eduardo N. Castanho, Helena Aidos, Sara C. Madeira:
Biclustering fMRI time series: a comparative study. BMC Bioinform. 23(1): 192 (2022)
[j35]
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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. J. Biomed. Informatics 134: 104172 (2022)
[j34]
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Marta D. M. Noronha, Rui Henriques, Sara C. Madeira, Luis E. Zárate:
Impact of metrics on biclustering solution and quality: A review. Pattern Recognit. 127: 108612 (2022)
[j33]
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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 Trans. Comput. Biol. Bioinform. 19(5): 2572-2583 (2022)
[j32]
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Francisco Neves, Anna Carolina Finamore, Sara C. Madeira, Rui Henriques:
Mining Actionable Patterns of Road Mobility From Heterogeneous Traffic Data Using Biclustering. IEEE Trans. Intell. Transp. Syst. 23(7): 6430-6445 (2022)
2021
[j31]
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João Lobo, Rui Henriques, Sara C. Madeira:
G-Tric: generating three-way synthetic datasets with triclustering solutions. BMC Bioinform. 22(1): 16 (2021)
[j30]
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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. J. Biomed. Informatics 117: 103730 (2021)
[j29]
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Rui Henriques, Sara C. Madeira:
FleBiC: Learning classifiers from high-dimensional biomedical data using discriminative biclusters with non-constant patterns. Pattern Recognit. 115: 107900 (2021)
2020
[j28]
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Telma Pereira, Sandra Cardoso, Manuela Guerreiro, Alexandre de Mendonça, Sara C. Madeira, Alzheimer's Disease Neuroimaging Initiative:
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. J. Biomed. Informatics 101: 103350 (2020)
2019
[j27]
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Rui Henriques, Sara C. Madeira:
Triclustering Algorithms for Three-Dimensional Data Analysis: A Comprehensive Survey. ACM Comput. Surv. 51(5): 95:1-95:43 (2019)
2018
[j26]
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Rui Henriques, Sara C. Madeira:
BSig: evaluating the statistical significance of biclustering solutions. Data Min. Knowl. Discov. 32(1): 124-161 (2018)
[j25]
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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 Decis. Mak. 18(1): 137:1-137:20 (2018)
2017
[j24]
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Rui Henriques, Francisco L. Ferreira, Sara C. Madeira:
BicPAMS: software for biological data analysis with pattern-based biclustering. BMC Bioinform. 18(1): 82:1-82:16 (2017)
[j23]
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Rui Henriques, Francisco L. Ferreira, Sara C. Madeira:
Erratum to: BicPAMS: software for biological data analysis with pattern-based biclustering. BMC Bioinform. 18(1): 162:1-162:2 (2017)
[j22]
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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 Decis. Mak. 17(1): 110:1-110:15 (2017)
2016
[j21]
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Rui Henriques, Sara C. Madeira:
BicNET: Flexible module discovery in large-scale biological networks using biclustering. Algorithms Mol. Biol. 11: 14 (2016)
[j20]
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Rui Henriques, Sara C. Madeira:
BiC2PAM: constraint-guided biclustering for biological data analysis with domain knowledge. Algorithms Mol. Biol. 11: 23 (2016)
2015
[j19]
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Rui Henriques, Sara C. Madeira, Cláudia Antunes:
Multi-period classification: learning sequent classes from temporal domains. Data Min. Knowl. Discov. 29(3): 792-819 (2015)
[j18]
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Rui Henriques, Cláudia Antunes, Sara C. Madeira:
Generative modeling of repositories of health records for predictive tasks. Data Min. Knowl. Discov. 29(4): 999-1032 (2015)
[j17]
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André Valério Carreiro, Pedro M. T. Amaral, Susana Pinto, Pedro Tomás, Mamede de Carvalho, Sara C. Madeira:
Prognostic models based on patient snapshots and time windows: Predicting disease progression to assisted ventilation in Amyotrophic Lateral Sclerosis. J. Biomed. Informatics 58: 133-144 (2015)
[j16]
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Rui Henriques, Cláudia Antunes, Sara C. Madeira:
A structured view on pattern mining-based biclustering. Pattern Recognit. 48(12): 3941-3958 (2015)
[j15]
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Rui Henriques, Sara C. Madeira:
Biclustering with Flexible Plaid Models to Unravel Interactions between Biological Processes. IEEE ACM Trans. Comput. Biol. Bioinform. 12(4): 738-752 (2015)
2014
[j14]
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Rui Henriques, Sara C. Madeira:
BicPAM: Pattern-based biclustering for biomedical data analysis. Algorithms Mol. Biol. 9: 27 (2014)
[j13]
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Rui Henriques, Sara C. Madeira:
BicSPAM: flexible biclustering using sequential patterns. BMC Bioinform. 15: 130 (2014)
[j12]
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  - journals/nar/TeixeiraMGGMSCPCFMOFS14
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Miguel Cacho Teixeira, Pedro Tiago Monteiro, Joana Fernandes Guerreiro, Joana Pinho Gonçalves, Nuno Pereira Mira, Sandra Costa dos Santos, Tânia Rodrigues Cabrito, Margarida Palma, Catarina Costa, Alexandre Paulo Francisco, Sara Cordeiro Madeira, Arlindo Limede Oliveira, Ana Teresa Freitas, Isabel Sá-Correia:
The YEASTRACT database: an upgraded information system for the analysis of gene and genomic transcription regulation in Saccharomyces cerevisiae. Nucleic Acids Res. 42(Database-Issue): 161-166 (2014)
[j11]
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Joana P. Gonçalves, Sara C. Madeira:
LateBiclustering: Efficient Heuristic Algorithm for Time-Lagged Bicluster Identification. IEEE ACM Trans. Comput. Biol. Bioinform. 11(5): 801-813 (2014)
2012
[j10]
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Joana P. Gonçalves, Yves Moreau, Sara C. Madeira:
AliBiMotif: Integrating alignment and biclustering to unravel transcription factor binding sites in DNA sequences. Int. J. Data Min. Bioinform. 6(2): 196-215 (2012)
[j9]
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André Valério Carreiro, Artur J. Ferreira, Mário A. T. Figueiredo, Sara Cordeiro Madeira:
Towards a Classification Approach using Meta-Biclustering: Impact of Discretization in the Analysis of Expression Time Series. J. Integr. Bioinform. 9(3) (2012)
2011
[j8]
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Joana P. Gonçalves, Alexandre P. Francisco, Nuno P. Mira, Miguel C. Teixeira, Isabel Sá-Correia, Arlindo L. Oliveira, Sara C. Madeira:
TFRank: network-based prioritization of regulatory associations underlying transcriptional responses. Bioinform. 27(22): 3149-3157 (2011)
[j7]
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André Valério Carreiro, Orlando Anunciação, João André Carriço, Sara Cordeiro Madeira:
Prognostic Prediction through Biclustering-Based Classification of Clinical Gene Expression Time Series. J. Integr. Bioinform. 8(3) (2011)
[j6]
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Dário Abdulrehman, Pedro T. Monteiro, Miguel C. Teixeira, Nuno P. Mira, Artur B. Lourenço, Sandra Costa dos Santos, Tânia Rodrigues Cabrito, Alexandre P. Francisco, Sara C. Madeira, Ricardo Santos Aires, Arlindo L. Oliveira, Isabel Sá-Correia, Ana T. Freitas:
YEASTRACT: providing a programmatic access to curated transcriptional regulatory associations in Saccharomyces cerevisiae through a web services interface. Nucleic Acids Res. 39(Database-Issue): 136-140 (2011)
[j5]
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Daniela Nitsch, Léon-Charles Tranchevent, Joana P. Gonçalves, Josef Korbinian Vogt, Sara C. Madeira, Yves Moreau:
PINTA: a web server for network-based gene prioritization from expression data. Nucleic Acids Res. 39(Web-Server-Issue): 334-338 (2011)
2010
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Ignacio Medina, José Carbonell, Luis Pulido, Sara C. Madeira, Stefan Götz, Ana Conesa, Joaquín Tárraga, Alberto D. Pascual-Montano, Rubén Nogales-Cadenas, Javier Santoyo, Francisco García-García, Martina Marbà, David Montaner, Joaquín Dopazo:
Babelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling. Nucleic Acids Res. 38(Web-Server-Issue): 210-213 (2010)
[j3]
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Sara C. Madeira, Miguel C. Teixeira, Isabel Sá-Correia, Arlindo L. Oliveira:
Identification of Regulatory Modules in Time Series Gene Expression Data Using a Linear Time Biclustering Algorithm. IEEE ACM Trans. Comput. Biol. Bioinform. 7(1): 153-165 (2010)
2009
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Sara C. Madeira, Arlindo L. Oliveira:
A polynomial time biclustering algorithm for finding approximate expression patterns in gene expression time series. Algorithms Mol. Biol. 4 (2009)
2004
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Sara C. Madeira, Arlindo L. Oliveira:
Biclustering Algorithms for Biological Data Analysis: A Survey. IEEE ACM Trans. Comput. Biol. Bioinform. 1(1): 24-45 (2004)

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2024
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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. CLEF (2) 2024: 118-139
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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. CLEF (Working Notes) 2024: 1312-1331
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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. CLEF (Working Notes) 2024: 1366-1379
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Helena Aidos, Roberto Bergamaschi, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Barbara Di Camillo, Mamede de Carvalho, Nicola Ferro, Piero Fariselli, Jose Manuel García Dominguez, Sara C. Madeira, Eleonora Tavazzi:
iDPP@CLEF 2024: The Intelligent Disease Progression Prediction Challenge. ECIR (6) 2024: 53-59
2023
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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. CLEF 2023: 343-369
[c38]
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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. CLEF (Working Notes) 2023: 1123-1164
[c37]
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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. CLEF (Working Notes) 2023: 1186-1198
[c36]
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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. CLEF (Working Notes) 2023: 1199-1209
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Helena Aidos, Roberto Bergamaschi, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Barbara Di Camillo, Mamede de Carvalho, Nicola Ferro, Piero Fariselli, Jose Manuel García Dominguez, Sara C. Madeira, Eleonora Tavazzi:
iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge. ECIR (3) 2023: 491-498
2022
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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. CLEF 2022: 395-422
[c33]
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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:
Overview of iDPP@CLEF 2022: The Intelligent Disease Progression Prediction Challenge. CLEF (Working Notes) 2022: 1130-1210
[c32]
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Ruben Branco, Diogo F. Soares, Andreia S. Martins, Eleonora Auletta, Eduardo N. Castanho, Susana Nunes, Filipa Serrano, Rita Torres Sousa, Catia Pesquita, Sara C. Madeira, Helena Aidos:
Hierarchical Modelling for ALS Prognosis: Predicting the Progression Towards Critical Events. CLEF (Working Notes) 2022: 1211-1227
[c31]
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Susana Nunes, Rita Torres 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. CLEF (Working Notes) 2022: 1256-1268
2020
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André Ferreira, Sara C. Madeira, Marta Gromicho, Mamede de Carvalho, Susana Vinga, Alexandra M. Carvalho:
Predictive Medicine Using Interpretable Recurrent Neural Networks. ICPR Workshops (1) 2020: 187-202
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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. IWBBIO 2020: 517-528
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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. IWBBIO 2020: 529-541
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Diogo F. 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. PACBB 2020: 112-122
2019
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João M. C. Sousa, Susana M. Vieira, João P. Carvalho, Sara C. Madeira, Leo A. Celi, Stan N. Finkelstein:
An Architecture Based on Fuzzy Systems for Personalized Medicine in ICUs. FUZZ-IEEE 2019: 1-6
2018
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Sofia Pires, Marta Gromicho, Susana Pinto, Mamede de Carvalho, Sara C. Madeira:
Predicting Non-invasive Ventilation in ALS Patients Using Stratified Disease Progression Groups. ICDM Workshops 2018: 748-757
2017
[c24]
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Telma Pereira, Alexandre de Mendonça, Francisco L. Ferreira, Sara C. Madeira, Manuela Guerreiro:
Towards a reliable prediction of conversion from Mild Cognitive Impairment to Alzheimer's Disease: stepwise learning using time windows. MIH@KDD 2017: 19-26
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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. PACBB 2017: 155-163
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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. PACBB 2017: 180-188
2015
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Rui Henriques, Sara C. Madeira:
Pattern-Based Biclustering with Constraints for Gene Expression Data Analysis. EPIA 2015: 326-339
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Rui Henriques, Sara C. Madeira:
BicNET: Efficient Biclustering of Biological Networks to Unravel Non-Trivial Modules. WABI 2015: 1-15
2014
[c19]
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André Vale, Sara C. Madeira, Cláudia Antunes:
Mining coherent evolution patterns in education through biclustering. EDM 2014: 391-392
2013
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Cecília Nunes, Dina Silva, Manuela Guerreiro, Alexandre de Mendonça, Alexandra M. Carvalho, Sara C. Madeira:
Class Imbalance in the Prediction of Dementia from Neuropsychological Data. EPIA 2013: 138-151
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Joana P. Gonçalves, Sara C. Madeira:
Heuristic approaches for time-lagged biclustering. BIOKDD 2013: 1-9
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Hugo López-Fernández, Miguel Reboiro-Jato, Sara C. Madeira, Rubén López-Cortés, J. D. Nunes-Miranda, Hugo Miguel Santos, Florentino Fdez-Riverola, Daniel Glez-Peña:
A Workflow for the Application of Biclustering to Mass Spectrometry Data. PACBB 2013: 145-153
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Rui Henriques, Cláudia Antunes, Sara C. Madeira:
Methods for the Efficient Discovery of Large Item-Indexable Sequential Patterns. NFMCP 2013: 100-116
2012
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André Valério Carreiro, Artur J. Ferreira, Mário A. T. Figueiredo, Sara C. Madeira:
Prognostic Prediction Using Clinical Expression Time Series: Towards a Supervised Learning Approach Based on Meta-biclusters. PACBB 2012: 11-20
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Filipe Cristóvão, Sara C. Madeira:
Parallel e-CCC-Biclustering: Mining Approximate Temporal Patterns in Gene Expression Time Series Using Parallel Biclustering. PACBB 2012: 21-31
2011
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Ricardo Santos Aires, João A. Carriço, Alexandre P. Francisco, Sara C. Madeira:
Baiacu: A Tool for the Visual Analysis of the Saccharomyces Cerevisiae Regulatory Network. PACBB 2011: 49-56
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André Valério Carreiro, Orlando Anunciação, João A. Carriço, Sara C. Madeira:
Biclustering-Based Classification of Clinical Expression Time Series: A Case Study in Patients with Multiple Sclerosis. PACBB 2011: 229-239
2010
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Joana P. Gonçalves, Sara C. Madeira:
e-BiMotif: Combining Sequence Alignment and Biclustering to Unravel Structured Motifs. IWPACBB 2010: 181-191
[c9]
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Joana P. Gonçalves, Sara C. Madeira, Yves Moreau:
Network-Based Disease Candidate Gene Prioritization: Towards Global Diffusion in Heterogeneous Association Networks. NyNaK 2010
2009
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Sara C. Madeira, Arlindo L. Oliveira:
Efficient Biclustering Algorithms for Time Series Gene Expression Data Analysis. IWANN (2) 2009: 1013-1019
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Paulo Moura, Ricardo Rocha, Sara C. Madeira:
High Level Thread-Based Competitive Or-Parallelism in Logtalk. PADL 2009: 107-121
2008
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Paulo Moura, Ricardo Rocha, Sara C. Madeira:
Thread-Based Competitive Or-Parallelism. ICLP 2008: 713-717
2007
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Sara C. Madeira, Arlindo L. Oliveira:
An Efficient Biclustering Algorithm for Finding Genes with Similar Patterns in Time-series Expression Data. APBC 2007: 67-80
2005
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Sara C. Madeira, Arlindo L. Oliveira:
A Linear Time Biclustering Algorithm for Time Series Gene Expression Data. WABI 2005: 39-52
2003
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Sara C. Madeira, Arlindo L. Oliveira, Catarina S. Conceição:
A Data Mining Approach to Credit Risk Evaluation and Behaviour Scoring. EPIA 2003: 184-188
[c2]
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João M. C. Sousa, Sara C. Madeira, Uzay Kaymak:
Modeling charity donations using target selection for revenue maximization. FUZZ-IEEE 2003: 654-659
2002
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João M. C. Sousa, Uzay Kaymak, Sara C. Madeira:
A comparative study of fuzzy target selection methods in direct marketing. FUZZ-IEEE 2002: 1251-1256

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2023
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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:
iDPP@CLEF 2023 - Participants' repositories for the Intelligent Disease Prediction Progression Challenge. Zenodo, 2023

Informal and Other Publications

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2022
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Miguel G. Silva, Rui Henriques, Sara C. Madeira:
User-Specific Bicluster-based Collaborative Filtering: Handling Preference Locality, Sparsity and Subjectivity. CoRR abs/2211.08366 (2022)
2019
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  - journals/corr/abs-1907-13070
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Telma Pereira, Sofia Pires, Marta Gromicho, Susana Pinto, Mamede de Carvalho, Sara C. Madeira:
Predicting assisted ventilation in Amyotrophic Lateral Sclerosis using a mixture of experts and conformal predictors. CoRR abs/1907.13070 (2019)
2018
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  - journals/corr/abs-1807-01619
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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. CoRR abs/1807.01619 (2018)

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