Blanda Mello

Blanda Mello, M. Sc.

Hello!

I am a Ph.D. student from Brazil and an FAU guest student at MaD Lab. My research focuses on Semantic Interoperability in Clinical Databases, a model based on NLP for information extraction in non-structured medical data, such as Electronic Health Records from Brazilian hospitals. This research is part of the MinhaSaudeDigital Project, Grant: CNPq-CAPES/Brazil.

I graduated in Development Systems and have an MSc. in Applied Computing in Artificial Intelligence focusing on Natural Language Generation. I have worked as a Python software engineer, database modeler, and team lead for web applications since 2015.

Curriculum Vitae

Since 2022 Interoperability Consultant at the Ministry of Health of Brazil, as interoperability business manager for information modeling on the National Health Data Network
Since 2020 Ph.D. Candidate in Applied Computing in Artificial Intelligence
2017-2019 M.Sc. in Applied Computing at Universidade do Vale do Rio dos Sinos UNISINOS
2013-2016 Associate Degree in System Development at Universidade Feevale

Publications

  • MELLO, B.H., Rigo, S.J., da Costa, C.A. et al. Semantic interoperability in health records standards: a systematic literature review. Health Technol. (2022). https://doi.org/10.1007/s12553-022-00639-w
  • SCHÜNKE, L. C.; MELLO, B.; COSTA, C. A.; ANTUNES, R. S.; RIGO, S. J.; RAMOS, G. O.; RIGHI, R. R.; SCHERER, J.N.; DONIDA, B. A Rapid Review of Machine Learning Approaches for Telemedicine in the Scope of COVID-19. Artificial Intelligence in Medicine, 2022. https://doi.org/10.1016/j.artmed.2022.102312
  • D. Silva, B. Mello, W. Fröhlich, S. Rigo, M. Schwertner, and C. Costa. “Avaliação de modelos para extração de dados não estruturados de um sistema EHR para atender a estrutura final de uma ontologia”, in Anais do XXII Simpósio Brasileiro de Computação Aplicada à Saúde, Teresina, 2022, pp. 437-448. https://doi.org/10.5753/sbcas.2022.222725
  • Bez, M.R., Mello, B., Pinheiro, D., Stahnke, F.R. e Barros, P.R. 2018. HEALTH SIMULATOR: um simulador de casos de estudo para a área da saúde. Revista Observatório. 4, 3 (abr. 2018), 283–306. https://doi.org/10.20873/uft.2447-4266.2018v4n3p283