Lightweight Automatic Error Detection by Monitoring Collar Variables. - João A. M. Santos; Rui Abreu 001 (ICTSS, 2012)

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)

Image descriptors in radiology images: a systematic review. - Mariana A. Nogueira; Pedro Henriques Abreu; Pedro Martins 003; Penousal Machado; Hugo Duarte; João A. M. Santos (Artif. Intell. Rev., 2017)

An artificial neural networks approach for assessment treatment response in oncological patients using PET/CT images. - Mariana A. Nogueira; Pedro Henriques Abreu; Pedro Martins 003; Penousal Machado; Hugo Duarte; João A. M. Santos (BMC Medical Imaging, 2017)

Interpreting deep learning models for ordinal problems. - José Pereira Amorim; Inês Domingues; Pedro Henriques Abreu; João A. M. Santos (ESANN, 2018)

Bi-Rads Classification of Breast Cancer: A New Pre-Processing Pipeline for Deep Models Training. - Inês Domingues; Pedro H. Abreu; João A. M. Santos (ICIP, 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)

Evaluation of Oversampling Data Balancing Techniques in the Context of Ordinal Classification. - Inês Domingues; José Pereira Amorim; Pedro H. Abreu; Hugo Duarte; João A. M. Santos (IJCNN, 2018)

Registration of CT with PET: A Comparison of Intensity-Based Approaches. - Gisèle Pereira; Inês Domingues; Pedro Martins 003; Pedro H. Abreu; Hugo Duarte; João A. M. Santos (IWCIA, 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)

Automatic Generation of Lymphoma Post-Treatment PETs using Conditional-GANs. - Gabriel Silva; Inês Domingues; Hugo Duarte; João A. M. Santos (DICTA, 2019)

Going Back to Basics on Volumetric Segmentation of the Lungs in CT: A Fully Image Processing Based Technique. - Ana Catarina Oliveira; Inês Domingues; Hugo Duarte; João A. M. Santos; Pedro H. Abreu (IbPRIA (2), 2019)

An iterative oversampling approach for ordinal classification. - Francisco Marques; Hugo Duarte; João A. M. Santos; Inês Domingues; José Pereira Amorim; Pedro H. Abreu (SAC, 2019)

Computer Vision in Esophageal Cancer: A Literature Review. - Inês Domingues; Inês Sampaio; Hugo Duarte; João A. M. Santos; Pedro H. Abreu (IEEE Access, 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)

Classification of oesophagic early-stage cancers: deep learning versus traditional learning approaches. - Jorge Ferreira; Inês Domingues; Olga Sousa; Inês Sampaio; João A. M. Santos (BIBE, 2020)

Interpretability vs. Complexity: The Friction in Deep Neural Networks. - José Pereira Amorim; Pedro H. Abreu; Mauricio Reyes 001; João A. M. Santos (IJCNN, 2020)

Using deep learning techniques in medical imaging: a systematic review of applications on CT and PET. - Inês Domingues; Gisèle Pereira; Pedro Martins 003; Hugo Duarte; João A. M. Santos; Pedro Henriques Abreu (Artif. Intell. Rev., 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)

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)

Many-objective optimization of a three-echelon supply chain: A case study in the pharmaceutical industry. - João A. M. Santos; João M. C. Sousa; Susana M. Vieira; André F. Ferreira (Comput. Ind. Eng., 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)

Evaluating Post-hoc Interpretability with Intrinsic Interpretability. - José Pereira Amorim; Pedro Henriques Abreu; João A. M. Santos; Henning Müller (CoRR, 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 001; João A. M. Santos (Inf. Fusion, 2023)

Evaluating the faithfulness of saliency maps in explaining deep learning models using realistic perturbations. - José Pereira Amorim; Pedro H. Abreu; João A. M. Santos; Marc Cortes; Victor Vila (Inf. Process. Manag., 2023)

Towards Sustainable Inventory Management: A Many-Objective Approach to Stock Optimization in Multi-Storage Supply Chains. - João A. M. Santos; Miguel S. E. Martins; Rui M. Pinto; Susana M. Vieira (Algorithms, 2024)