Miriam Seoane Santos

According to our database, Miriam Seoane Santos authored at least 21 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

An Interpretable Human-in-the-Loop Process to Improve Medical Image Classification.

Joana Cristo Santos, Miriam Seoane Santos, Pedro Henriques Abreu

Proceedings of the Advances in Intelligent Data Analysis XXII, 2024

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, October, 2023

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, João A. M. Santos

Inf. Fusion, 2023

2022

The impact of heterogeneous distance functions on missing data imputation and classification performance.

Miriam Seoane Santos, Pedro Henriques Abreu, Alberto Fernández, Julián Luengo, João A. M. Santos

Eng. Appl. Artif. Intell., 2022

On the joint-effect of class imbalance and overlap: a critical review.

Miriam Seoane Santos, Pedro Henriques Abreu, Nathalie Japkowicz, Alberto Fernández, Carlos Soares, Szymon Wilk, João A. M. Santos

Artif. Intell. Rev., 2022

The identification of cancer lesions in mammography images with missing pixels: analysis of morphology.

Joana Cristo Santos, Pedro Henriques Abreu, Miriam Seoane Santos

Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics, 2022

2021

FAWOS: Fairness-Aware Oversampling Algorithm Based on Distributions of Sensitive Attributes.

Teresa Salazar, Miriam Seoane Santos, Helder Araújo, Pedro Henriques Abreu

IEEE Access, 2021

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

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

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

Proceedings of the Artificial Intelligence in Medicine, 2020

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

MNAR Imputation with Distributed Healthcare Data.

Ricardo Cardoso Pereira, Miriam Seoane Santos, Pedro Pereira Rodrigues, Pedro Henriques Abreu

Proceedings of the Progress in Artificial Intelligence, 2019

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

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

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

Proceedings of the Advances in Intelligent Data Analysis XVII, 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

Proceedings of the Advances in Intelligent Data Analysis XVII, 2018

Missing Data Imputation via Denoising Autoencoders: The Untold Story.

Adriana Fonseca Costa, Miriam Seoane Santos, Jastin Pompeu Soares, Pedro Henriques Abreu

Proceedings of the Advances in Intelligent Data Analysis XVII, 2018

2017

HCC Survival.

Miriam Seoane Santos, Pedro H. Abreu, Pedro J. García-Laencina, Adélia Simão, Armando Carvalho

Dataset, November, 2017

Influence of Data Distribution in Missing Data Imputation.

Miriam Seoane Santos, Jastin Pompeu Soares, Pedro Henriques Abreu, Hélder Araújo, João A. M. Santos

Proceedings of the Artificial Intelligence in Medicine, 2017

2016

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

2015

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