Using Machine Learning to support health system planning during the Covid-19 pandemic: a case study using data from São José dos Campos (Brazil). - Leila Abuabara; Maria Gabriela Valeriano; Carlos Roberto Veiga Kiffer; Horacio Hideki Yanasse; Ana Carolina Lorena (CLEI Electron. J., 2021)

Let the data speak: analysing data from multiple health centers of the São Paulo metropolitan area for COVID-19 clinical deterioration prediction. - Maria Gabriela Valeriano; Carlos Roberto Veiga Kiffer; Giane Higino; Paloma Zanão; Dulce A. Barbosa; Patrícia A. Moreira; Paulo Caleb J. L. Santos; Renato Grinbaum; Ana Carolina Lorena (CCGRID, 2022)

A Framework for Characterizing What Makes an Instance Hard to Classify. - Maria Gabriela Valeriano; Pedro Yuri Arbs Paiva; Carlos Roberto Veiga Kiffer; Ana Carolina Lorena (BRACIS (2), 2023)

Explaining instances in the health domain based on the exploration of a dataset's hardness embedding. - Maria Gabriela Valeriano; João Luiz Junho Pereira; Carlos Roberto Veiga Kiffer; Ana Carolina Lorena (GECCO Companion, 2024)

Understanding the performance of machine learning models from data- to patient-level. - Maria Gabriela Valeriano; Ana Matran-Fernandez; Carlos Roberto Veiga Kiffer; Ana Carolina Lorena (ACM J. Data Inf. Qual., 2024)