| Texto completo | |
| Autor(es): |
Andrade Silva, Joao Flavio
;
Izbicki, Rafael
;
Bastos, Leonardo S.
;
Soares, Guilherme P.
Número total de Autores: 4
|
| Tipo de documento: | Artigo Científico |
| Fonte: | DEVELOPMENTS IN STATISTICAL MODELLING, IWSM 2024; v. N/A, p. 6-pg., 2024-01-01. |
| Resumo | |
We introduce a novel methodology for estimating the distribution of viruses in Severe Acute Respiratory Syndrome (SARS) patients in Brazil, addressing significant challenges for data in that country, such as data delays and the absence of negative test results. By employing a probabilistic classifier, our approach offers precise, adaptable estimates across various demographic characteristics and regions of the country without the need for predefined groups. Comparative analyses demonstrate the effectiveness of the model. This methodology significantly contributes to public health by enhancing disease monitoring and supporting targeted prevention strategies. (AU) | |
| Processo FAPESP: | 23/07068-1 - Aprendizado estatístico de máquina: em direção a uma melhor quantificação de incerteza |
| Beneficiário: | Rafael Izbicki |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |