Cecilia Cordeiro da Silva
Biographic Data
| ID | 9994481 |
|---|---|
| NAME | Cecilia Cordeiro da Silva |
| GIVEN NAMES | Cecilia Cordeiro |
| FAMILY NAME | da Silva |
| SIGNATURE | DA SILVA C C |
| AFFILIATIONS | Universidade Federal de Pernambuco |
| ORCID | 0000-0002-7061-8477 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Temporal and Spatiotemporal Arboviruses Forecasting by Machine Learning
Arboviruses are a group of diseases that are transmitted by an arthropod vector. Since they are part of the Neglected Tropical Diseases that pose several public health challenges for countries around the world. The arboviruses' dynamics are governed by a combination of climatic, environmental, and human mobility factors. Arboviruses prediction models can be a support tool for decision-making by public health agents. In this study, we propose a sy…
Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting
Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post—the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases …
Covid-Sgis
Background: The global burden of the new coronavirus SARS-CoV-2 is increasing at an unprecedented rate. The current spread of Covid-19 in Brazil is problematic causing a huge public health burden to its population and national health-care service. To evaluate strategies for alleviating such problems, it is necessary to forecast the number of cases and deaths in order to aid the stakeholders in the process of making decisions against the disease. …
No prominent works on this page.
Covid-Sgis
Background: The global burden of the new coronavirus SARS-CoV-2 is increasing at an unprecedented rate. The current spread of Covid-19 in Brazil is problematic causing a huge public health burden to its population and national health-care service. To evaluate strategies for alleviating such problems, it is necessary to forecast the number of cases and deaths in order to aid the stakeholders in the process of making decisions against the disease. …
Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting
Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post—the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases …
Temporal and Spatiotemporal Arboviruses Forecasting by Machine Learning
Arboviruses are a group of diseases that are transmitted by an arthropod vector. Since they are part of the Neglected Tropical Diseases that pose several public health challenges for countries around the world. The arboviruses' dynamics are governed by a combination of climatic, environmental, and human mobility factors. Arboviruses prediction models can be a support tool for decision-making by public health agents. In this study, we propose a sy…
Anomaly Detection Techniques and Applications (2 works) · Computer Science (2 works) · Medicine (2 works) · 2019-20 coronavirus outbreak (1 work) · Autoregressive integrated moving average (1 work) · COVID-19 diagnosis using AI (1 work) · COVID-19 epidemiological studies (1 work) · Data mining (1 work) · Data-Driven Disease Surveillance (1 work) · Disease (1 work)