Análise de Sentimento em Redes Sociais para a Língua Portuguesa Utilizando Algoritmos de Classificação. - Erikson Júlio De Aguiar; Bruno S. Faiçal; Jó Ueyama; Glauco Carlos Silva; André Luís Andrade Menolli (SBRC, 2018)

A Survey of Blockchain-Based Strategies for Healthcare. - Erikson Júlio De Aguiar; Bruno S. Faiçal; Bhaskar Krishnamachari; Jó Ueyama (ACM Comput. Surv., 2021)

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 Júlio De Aguiar; Ivar Vargas Belizario; Márcus V. L. Costa; Jamilly G. Maciel; Mirela T. Cazzolato; Caetano Traina; Marcello H. Nogueira-Barbosa; Agma J. M. Traina (CBMS, 2022)

Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases. - Erikson Júlio De Aguiar; Karem D. Marcomini; Felipe A. Quirino; Marco A. Gutierrez 001; Caetano Traina Jr.; Agma J. M. Traina (Computer-Aided Diagnosis, 2022)

A blockchain-based protocol for tracking user access to shared medical imaging. - Erikson Júlio De Aguiar; Alyson de Jesus dos Santos; Rodolfo I. Meneguette; Robson E. De Grande; Jó Ueyama (Future Gener. Comput. Syst., 2022)

Assessing Vulnerabilities of Deep Learning Explainability in Medical Image Analysis Under Adversarial Settings. - Erikson Júlio De Aguiar; Márcus V. L. Costa; Caetano Traina; Agma J. M. Traina (CBMS, 2023)

A Deep Learning-based Radiomics Approach for COVID-19 Detection from CXR Images using Ensemble Learning Model. - Márcus V. L. Costa; Erikson Júlio De Aguiar; Lucas Santiago Rodrigues; Jonathan S. Ramos; Caetano Traina; Agma J. M. Traina (CBMS, 2023)

MedTimeSplit: Continual dataset partitioning to mimic real-world settings for federated learning on Non-IID medical image data. - Erikson Júlio De Aguiar; Agma J. M. Traina; Sumi Helal (IEEE Big Data, 2024)

RADAR-MIX: How to Uncover Adversarial Attacks in Medical Image Analysis through Explainability. - Erikson Júlio De Aguiar; Caetano Traina; Agma J. M. Traina (CBMS, 2024)

AI-Driven Public Health Surveillance: Analyzing Vulnerable Areas in Brazil Using Remote Sensing and Socioeconomic Data. - Joao Pedro Silva; Erikson Júlio De Aguiar; Gabriel Spadon; Agma J. M. Traina; Jose F. Rodrigues (CBMS, 2025)

DEELE-Rad: exploiting deep radiomics features in deep learning models using COVID-19 chest X-ray images. - Márcus V. L. Costa; Erikson Júlio De Aguiar; Lucas Santiago Rodrigues; Caetano Traina; Agma J. M. Traina (Health Inf. Sci. Syst., 2025)