Publications

Erikson J de Aguiar, Márcus VL Costa, Caetano Traina, Agma JM Traina (2023). Assessing Vulnerabilities of Deep Learning Explainability in Medical Image Analysis Under Adversarial Settings. CBMS'23.

Márcus VL Costa, Erikson J de Aguiar, Jonathan S Ramos, Lucas Santiago, Caetano Traina, Agma JM Traina (2023). A Deep Learning-based Radiomics Approach for COVID-19 Detection from CXR Images using Ensemble Learning Model. CBMS'23.

Erikson J de Aguiar, Caetano Traina, Agma JM Traina (2023). Security and Privacy in Machine Learning for Health Systems: Strategies and Challenges. IMIA'23.

Jonathan S Ramos, Erikson J de Aguiar, Ivar V Belizario, Márcus VL Costa, Jamilly G Maciel, Mirela T Cazzolato, Caetano Traina, Marcello H Nogueira-Barbosa, Agma JM Traina (2022). Analysis of vertebrae without fracture on spine MRI to assess bone fragility: A Comparison of Traditional Machine Learning and Deep Learning. CBMS'22.

Erikson J Aguiar, Alyson J Dos Santos, Rodolfo I Meneguette, Robson De Grade, Jó Ueyama (2022). A blockchain-based protocol for tracking user access to shared medical imaging. FGCS.

Erikson Aguiar, Karem Marcomini, Felipe Quirino, Marco Gutierrez, Caetano Traina Jr, Agma Traina (2022). Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases. SPIE Medical Imaging, 2022.

Erikson Júlio De Aguiar, Bruno S Faiçal, Bhaskar Krishnamachari, Jó Ueyama (2020). A Survey of Blockchain-Based Strategies for Healthcare. CSUR.

Erikson Júlio De Aguiar, Bruno S. Faiçal, Jó Ueyama, Glauco Carlos Silva, André Menolli (2018). Análise de Sentimento em Redes Sociais para a Língua Portuguesa Utilizando Algoritmos de Classificação. SBRC'18.