| 2025 | CBMS | AI-Driven Public Health Surveillance: Analyzing Vulnerable Areas in Brazil Using Remote Sensing and Socioeconomic Data. | Joao Pedro Silva, Erikson Jlio De Aguiar, Gabriel Spadon, Agma J. M. Traina, Jose F. Rodrigues |
| 2024 | CBMS | RADAR-MIX: How to Uncover Adversarial Attacks in Medical Image Analysis through Explainability. | Erikson Jlio De Aguiar, Caetano Traina, Agma J. M. Traina |
| 2023 | CBMS | Assessing Vulnerabilities of Deep Learning Explainability in Medical Image Analysis Under Adversarial Settings. | Erikson Jlio De Aguiar, Mrcus V. L. Costa, Caetano Traina, Agma J. M. Traina |
| 2023 | CBMS | A Deep Learning-based Radiomics Approach for COVID-19 Detection from CXR Images using Ensemble Learning Model. | Mrcus V. L. Costa, Erikson Jlio De Aguiar, Lucas Santiago Rodrigues, Jonathan S. Ramos, Caetano Traina, Agma J. M. Traina |
| 2022 | CBMS | Analysis of vertebrae without fracture on spine MRI to assess bone fragility: A Comparison of Traditional Machine Learning and Deep Learning. | Jonathan S. Ramos, Erikson Jlio De Aguiar, Ivar Vargas Belizario, Mrcus V. L. Costa, Jamilly G. Maciel, Mirela T. Cazzolato, Caetano Traina, Marcello H. Nogueira-Barbosa, Agma J. M. Traina |