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2020 – today
- 2023
[c7]Angelo Rossini, Domingos Alves, Victor Cassão, Newton Shydeo Brandão Miyoshi:
Unsupervised K-means Analysis of Tuberculosis Data in Brazil: Identifying High Prevalence States and Temporal Trends. CENTERIS/ProjMAN/HCist 2023: 1839-1846- [c6]Victor Cassão
, Filipe Andrade Bernardi, Vinícius Costa Lima, Giovane Thomazini Soares, Newton Shydeo Brandão Miyoshi, Ana Clara de Andrade Mioto, Afrânio Lineu Kritski, Domingos Alves:
A Web Portal for Real-Time Data Quality Analysis on the Brazilian Tuberculosis Research Network: A Case Study. ICCS (3) 2023: 300-312 - [c5]Filipe Andrade Bernardi, Vinícius Lima, Gabriel Sartoretto, João Baiochi, Victor Cassão, Afrânio Lineu Kritski, Rui Rijo, Domingos Alves:
From Raw Data to FAIR Data: The FAIRification Workflow for Brazilian Tuberculosis Research. ICIMTH 2023: 331-334 - [c4]Mariana Tavares Mozini, Filipe Andrade Bernardi, Ana Clara de Andrade Mioto, Victor Cassão, Afrânio Lineu Kritski, Domingos Alves:
A Computational Infrastructure for Analyzing Tuberculosis Research Data in Brazil. ICIMTH 2023: 558-561 - 2022
- [c3]Ana Clara de Andrade Mioto, Mariana Tavares Mozini, Renan Barbieri Segamarchi, Giovane Thomazini Soares, Pedro Emilio Andrade Martins, Victor Cassão, Luís Gustavo Barichello Ferrassini, Newton Shydeo Brandão Miyoshi, Domingos Alves, Lariza Laura de Oliveira:
Preliminary Results to Predict Tuberculosis Outcomes Applying Traditional and Automated Machine Learning Models. CENTERIS/ProjMAN/HCist 2022: 1365-1372 - [c2]Victor Cassão, Domingos Alves, Ana Clara de Andrade Mioto, Mariana Tavares Mozini, Renan Barbieri Segamarchi, Newton Shydeo Brandão Miyoshi:
Unsupervised analysis of COVID-19 pandemic evolution in brazilian states: Vaccination Scenario. CENTERIS/ProjMAN/HCist 2022: 1453-1461 - 2021
- [c1]Victor Cassão, Domingos Alves, Ana Clara de Andrade Mioto, Filipe Andrade Bernardi, Newton Shydeo Brandão Miyoshi:
Unsupervised analysis of COVID-19 pandemic evolution in brazilian states. CENTERIS/ProjMAN/HCist 2021: 655-662
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