A new cluster-based oversampling method for improving survival prediction of hepatocellular carcinoma patients. - Miriam Seoane Santos; Pedro Henriques Abreu; Pedro J. García-Laencina; Adélia Simão; Armando Carvalho (J. Biomed. Informatics, 2015)

Predicting Breast Cancer Recurrence Using Machine Learning Techniques: A Systematic Review. - Pedro Henriques Abreu; Miriam Seoane Santos; Miguel Henriques Abreu; Bruno Andrade; Daniel Castro Silva (ACM Comput. Surv., 2016)

Influence of Data Distribution in Missing Data Imputation. - Miriam Seoane Santos; Jastin Pompeu Soares; Pedro Henriques Abreu; Hélder Araújo; João A. M. Santos (AIME, 2017)

HCC Survival. - Miriam Seoane Santos; Pedro H. Abreu; Pedro J. García-Laencina; Adélia Simão; Armando Carvalho (UCI Machine Learning Repository, 2017)

Missing Data Imputation via Denoising Autoencoders: The Untold Story. - Adriana Fonseca Costa; Miriam Seoane Santos; Jastin Pompeu Soares; Pedro Henriques Abreu (IDA, 2018)

Analysing the Footprint of Classifiers in Overlapped and Imbalanced Contexts. - Marta Mercier; Miriam Seoane Santos; Pedro H. Abreu; Carlos Soares; Jastin Pompeu Soares; João A. M. Santos (IDA, 2018)

Exploring the Effects of Data Distribution in Missing Data Imputation. - Jastin Pompeu Soares; Miriam Seoane Santos; Pedro Henriques Abreu; Hélder Araújo; João A. M. Santos (IDA, 2018)

Cross-Validation for Imbalanced Datasets: Avoiding Overoptimistic and Overfitting Approaches [Research Frontier]. - Miriam Seoane Santos; Jastin Pompeu Soares; Pedro Henriques Abreu; Hélder Araújo; João A. M. Santos (IEEE Comput. Intell. Mag., 2018)

Improving the Classifier Performance in Motor Imagery Task Classification: What are the steps in the classification process that we should worry about? - Miriam Seoane Santos; Pedro H. Abreu; Germán Rodríguez-Bermúdez; Pedro J. García-Laencina (Int. J. Comput. Intell. Syst., 2018)

MNAR Imputation with Distributed Healthcare Data. - Ricardo Cardoso Pereira; Miriam Seoane Santos; Pedro Pereira Rodrigues; Pedro Henriques Abreu (EPIA (2), 2019)

Generating Synthetic Missing Data: A Review by Missing Mechanism. - Miriam Seoane Santos; Ricardo Cardoso Pereira; Adriana Fonseca Costa; Jastin Pompeu Soares; João A. M. Santos; Pedro Henriques Abreu (IEEE Access, 2019)

Assessing the Impact of Distance Functions on K-Nearest Neighbours Imputation of Biomedical Datasets. - Miriam Seoane Santos; Pedro H. Abreu; Szymon Wilk; João A. M. Santos (AIME, 2020)

Reviewing Autoencoders for Missing Data Imputation: Technical Trends, Applications and Outcomes. - Ricardo Cardoso Pereira; Miriam Seoane Santos; Pedro Pereira Rodrigues; Pedro Henriques Abreu (J. Artif. Intell. Res., 2020)

How distance metrics influence missing data imputation with k-nearest neighbours. - Miriam Seoane Santos; Pedro Henriques Abreu; Szymon Wilk; João A. M. Santos (Pattern Recognit. Lett., 2020)

FAWOS: Fairness-Aware Oversampling Algorithm Based on Distributions of Sensitive Attributes. - Teresa Salazar; Miriam Seoane Santos; Helder Araújo; Pedro Henriques Abreu (IEEE Access, 2021)

The identification of cancer lesions in mammography images with missing pixels: analysis of morphology. - Joana Cristo Santos; Pedro Henriques Abreu; Miriam Seoane Santos (DSAA, 2022)

On the joint-effect of class imbalance and overlap: a critical review. - Miriam Seoane Santos; Pedro Henriques Abreu; Nathalie Japkowicz; Alberto Fernández 001; Carlos Soares; Szymon Wilk; João A. M. Santos (Artif. Intell. Rev., 2022)

The impact of heterogeneous distance functions on missing data imputation and classification performance. - Miriam Seoane Santos; Pedro Henriques Abreu; Alberto Fernández 001; Julián Luengo; João A. M. Santos (Eng. Appl. Artif. Intell., 2022)

A unifying view of class overlap and imbalance: Key concepts, multi-view panorama, and open avenues for research. - Miriam Seoane Santos; Pedro Henriques Abreu; Nathalie Japkowicz; Alberto Fernández 001; João A. M. Santos (Inf. Fusion, 2023)

ydata-profiling: Accelerating data-centric AI with high-quality data. - Fabiana Clemente; Gonçalo Martins Ribeiro; Alexandre Quemy; Miriam Seoane Santos; Ricardo Cardoso Pereira; Alex Barros (Neurocomputing, 2023)

Reconstruction of Mammography Projections using Image-to-Image Translation Techniques. - Joana Cristo Santos; Miriam Seoane Santos; Pedro Henriques Abreu (ESANN, 2024)

An Interpretable Human-in-the-Loop Process to Improve Medical Image Classification. - Joana Cristo Santos; Miriam Seoane Santos; Pedro Henriques Abreu (IDA (1), 2024)

A Label Propagation Approach for Missing Data Imputation. - Filipe Loyola Lopes; Arthur Dantas Mangussi; Ricardo Cardoso Pereira; Miriam Seoane Santos; Pedro Henriques Abreu; Ana Carolina Lorena (IEEE Access, 2025)

Studying the robustness of data imputation methodologies against adversarial attacks. - Arthur Dantas Mangussi; Ricardo Cardoso Pereira; Ana Carolina Lorena; Miriam Seoane Santos; Pedro Henriques Abreu (Comput. Secur., 2025)

Pycol: A Python package for dataset complexity measures. - Diogo Apóstolo; Miriam Seoane Santos; Ana Carolina Lorena; Pedro Henriques Abreu (Neurocomputing, 2025)

mdatagen: A python library for the artificial generation of missing data. - Arthur Dantas Mangussi; Miriam Seoane Santos; Filipe Loyola Lopes; Ricardo Cardoso Pereira; Ana Carolina Lorena; Pedro Henriques Abreu (Neurocomputing, 2025)

The Role of Deep Learning in Medical Image Inpainting: A Systematic Review. - Joana Cristo Santos; Hugo Tomás Pereira Alexandre; Miriam Seoane Santos; Pedro Henriques Abreu (ACM Trans. Comput. Heal., 2025)