Erikson Júlio De Aguiar

According to our database, Erikson Júlio De Aguiar authored at least 11 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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., December, 2025

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

Proceedings of the 38th IEEE International Symposium on Computer-Based Medical Systems, 2025

2024

RADAR-MIX: How to Uncover Adversarial Attacks in Medical Image Analysis through Explainability.

Erikson Júlio De Aguiar, Caetano Traina, Agma J. M. Traina

Proceedings of the 37th IEEE International Symposium on Computer-Based Medical Systems, 2024

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

Proceedings of the IEEE International Conference on Big Data, 2024

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

Proceedings of the 36th IEEE International Symposium on Computer-Based Medical Systems, 2023

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

Proceedings of the 36th IEEE International Symposium on Computer-Based Medical Systems, 2023

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

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, Caetano Traina Jr., Agma J. M. Traina

Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022

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

Proceedings of the 35th IEEE International Symposium on Computer-Based Medical Systems, 2022

2021

A Survey of Blockchain-Based Strategies for Healthcare.

Erikson Júlio De Aguiar, Bruno S. Faiçal, Bhaskar Krishnamachari, Jó Ueyama

ACM Comput. Surv., 2021

2018

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

Proceedings of the XXXVI Brazilian Symposium on Computer Networks and Distributed Systems, 2018