Angelo A. Duarte

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Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and(More)
BACKGROUND Leishmaniasis is caused by intracellular Leishmania parasites that induce a T-cell mediated response associated with recognition of CD4+ and CD8+ T cell Line 1Lineepitopes. Identification of CD8+ antigenic determinants is crucial for vaccine and therapy development. Herein, we developed an open-source software dedicated to search and compile data(More)
PathoSpotter is a computational system designed to assist pathologists in teaching about and researching kidney diseases. PathoSpotter-K is the version that was developed to detect nephrological lesions in digital images of kidneys. Here, we present the results obtained using the first version of PathoSpotter-K, which uses classical image processing and(More)
BACKGROUND The witches' broom disease is a plague caused by Moniliophthora perniciosa in the Theobroma cacao, which has been reducing the cocoa production since 1989. This issue motivated a genome project that has showing several new molecular targets, which can be developed inhibitors in order to control the plague. Among the molecular targets obtained,(More)
In the preset study, Artificial Neural Network (ANN) and Bayesian Network (BN) techniques are evaluated as supporting tools for the diagnosis of asymptomatic malaria infection. These techniques are compared with two classical laboratorial tests for diagnosis of malaria: the light microscopy and the Nested PCR. To do this, the tests were run in a group of(More)
This paper presents the current results in the detection of segmental glomerulosclerosis by analyzing histological images of kidney biopsies, stained using hematoxylin and eosin (H&E) or periodic acidSchiff (PAS) techniques. The work is part of the development of the PathoSpotter-K system, which aims the detection of elemental lesions in histological images(More)
The paper “Prediction of Kidney Function from Biopsy Images using Convolutional Neural Networks” by Ledbetter et al. (2017)(Ledbetter et al., 2017) deals with the interesting subject of automatized estimate of kidney function from histological images. The authors report that using Convolutional Neural Network (CNN) associated with some image processing(More)
There are grant numbers missing from the Funding section. The correct funding information is as follows: This work was supported with grants from FAPESB (Fundação de Amparo à Pes-quisa da Bahia) (SUS0003/2009, DCR002/2011 and RED0018/2013). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the(More)
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