Amauri Duarte Da Silva
Biographic Data
| ID | 3667197 |
|---|---|
| NAME | Amauri Duarte Da Silva |
| GIVEN NAMES | Amauri Duarte |
| FAMILY NAME | Da Silva |
| SIGNATURE | DA SILVA A D |
| AFFILIATIONS | Universidade Federal de Ciências da Saúde de Porto Alegre |
| ORCID | 0000-0001-6395-458X |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Machine learning in predicting severe acute respiratory infection outbreaks
Severe acute respiratory infection (SARI) outbreaks occur annually, with seasonal peaks varying among geographic regions. Case notification is important to prepare healthcare networks for patient attendance and hospitalization. Thus, health managers need adequate resource planning tools for SARI seasons. This study aims to predict SARI outbreaks based on models generated with machine learning using SARI hospitalization notification data. In this …
Severe acute respiratory infection surveillance in Brazil
Epidemiological surveillance and notification of respiratory infections are important for management and control of epidemics and pandemics. Fact-based decisions, like social distancing policies and preparation of hospital beds, are taken based on several factors, including case numbers; hence, health authorities need quick access to reliable and well-analysed data. We aimed to analyse the role of the Brazilian public health system in the notific…
No prominent works on this page.
Severe acute respiratory infection surveillance in Brazil
Epidemiological surveillance and notification of respiratory infections are important for management and control of epidemics and pandemics. Fact-based decisions, like social distancing policies and preparation of hospital beds, are taken based on several factors, including case numbers; hence, health authorities need quick access to reliable and well-analysed data. We aimed to analyse the role of the Brazilian public health system in the notific…
Machine learning in predicting severe acute respiratory infection outbreaks
Severe acute respiratory infection (SARI) outbreaks occur annually, with seasonal peaks varying among geographic regions. Case notification is important to prepare healthcare networks for patient attendance and hospitalization. Thus, health managers need adequate resource planning tools for SARI seasons. This study aims to predict SARI outbreaks based on models generated with machine learning using SARI hospitalization notification data. In this …
COVID-19 epidemiological studies (2 works) · Incidence (geometry) (2 works) · Medicine (2 works) · Artificial neural network (1 works) · Attendance (1 works) · Computer Science (1 works) · Coronavirus disease 2019 (COVID-19) (1 works) · COVID-19 and healthcare impacts (1 works) · COVID-19 diagnosis using AI (1 works) · Data-Driven Disease Surveillance (1 works)