Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 3 de 3
Filtrar
Mais filtros











Base de dados
Intervalo de ano de publicação
1.
Epidemiol Infect ; 148: e295, 2020 12 02.
Artigo em Inglês | MEDLINE | ID: mdl-33261679

RESUMO

Two hundred days after the first confirmed case of COVID-19 in Brazil, the epidemic has rapidly spread in metropolitan areas and advanced throughout the countryside. We followed the temporal epidemic pattern at São Paulo State, the most populous of the country, the first to have a confirmed case of COVID-19, and the one with the most significant number of cases until now. We analysed the number of new cases per day in each regional health department and calculated the effective reproduction number (Rt) over time. Social distance measures, along with improvement in testing and isolating positive cases, general population mask-wearing and standard health security protocols for essential and non-essential activities, were adopted and impacted on slowing down epidemic velocity but were insufficient to stop transmission.


Assuntos
COVID-19/epidemiologia , Epidemias/estatística & dados numéricos , Número Básico de Reprodução , Brasil/epidemiologia , Humanos , SARS-CoV-2
2.
Epidemiol Infect ; 148: e178, 2020 08 18.
Artigo em Inglês | MEDLINE | ID: mdl-32807244

RESUMO

Different countries have adopted strategies for the early detection of SARS-CoV-2 since the declaration of community transmission by the World Health Organization (WHO) and timely diagnosis has been considered one of the major obstacles for surveillance and healthcare. Here, we report the increase of the number of laboratories to COVID-19 diagnosis in Brazil. Our results demonstrate an increase and decentralisation of certified laboratories, which does not match the much higher increase in the number of COVID-19 cases. Also, it becomes clear that laboratories are irregularly distributed over the country, with a concentration in the most developed state, São Paulo.


Assuntos
Técnicas de Laboratório Clínico/estatística & dados numéricos , Infecções por Coronavirus/diagnóstico , Laboratórios/provisão & distribuição , Pneumonia Viral/diagnóstico , Betacoronavirus , Brasil/epidemiologia , COVID-19 , Teste para COVID-19 , Infecções por Coronavirus/epidemiologia , Humanos , Incidência , Técnicas de Diagnóstico Molecular , Pandemias , Pneumonia Viral/epidemiologia , SARS-CoV-2
3.
Sensors (Basel) ; 18(12)2018 Dec 15.
Artigo em Inglês | MEDLINE | ID: mdl-30558278

RESUMO

In this study, we developed an online graphical and intuitive interface connected to a server aiming to facilitate professional access worldwide to those facing problems with bovine blastocysts classification. The interface Blasto3Q, where 3Q refers to the three qualities of the blastocyst grading, contains a description of 24 variables that were extracted from the image of the blastocyst and analyzed by three Artificial Neural Networks (ANNs) that classify the same loaded image. The same embryo (i.e., the biological specimen) was submitted to digital image capture by the control group (inverted microscope with 40× magnification) and the experimental group (stereomicroscope with maximum of magnification plus 4× zoom from the cell phone camera). The images obtained from the control and experimental groups were uploaded on Blasto3Q. Each image from both sources was evaluated for segmentation and submitted (only if it could be properly or partially segmented) for automatic quality grade classification by the three ANNs of the Blasto3Q program. Adjustments on the software program through the use of scaling algorithm software were performed to ensure the proper search and segmentation of the embryo in the raw images when they were captured by the smartphone, since this source produced small embryo images compared with those from the inverted microscope. With this new program, 77.8% of the images from smartphones were successfully segmented and from those, 85.7% were evaluated by the Blasto3Q in agreement with the control group.


Assuntos
Inteligência Artificial , Smartphone , Software , Algoritmos , Animais , Blastocisto/citologia , Bovinos , Redes Neurais de Computação
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA