Institution
Universidade Federal de Minas Gerais
Education•Belo Horizonte, Minas Gerais, Brazil•
About: Universidade Federal de Minas Gerais is a education organization based out in Belo Horizonte, Minas Gerais, Brazil. It is known for research contribution in the topics: Population & Immune system. The organization has 41631 authors who have published 75688 publications receiving 1249905 citations.
Papers published on a yearly basis
Papers
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TL;DR: A structure for simulating urban change based on estimating land use transitions using elementary probabilistic methods which draw their inspiration from Bayes’ theory and the related ‘weights of evidence’ approach is proposed.
227 citations
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TL;DR: An en bloc assessment of a set of previously described biomarkers in different mood states as well as in healthy subjects, finding several of the markers discriminated between the bipolar and control groups, especially when patients were in acute episodes.
227 citations
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TL;DR: In this article, the authors discuss the relationship between schooling and youth and the place of schools in the socialization of contempo- rary youth, especially in what regards young people from lower
Abstract: This text discusses the relationships between schooling and youth and the place of schools in the socialization of contempo- rary youth, especially in what regards young people from lower
227 citations
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TL;DR: In this paper, a deep neural network (DNN) was used to detect 6 types of abnormalities in 12-lead ECG recordings, with F1 scores above 80% and specificity over 99%.
Abstract: The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has recently achieved striking success in a variety of task and there are great expectations on how it might improve clinical practice. Here we present a DNN model trained in a dataset with more than 2 million labeled exams analyzed by the Telehealth Network of Minas Gerais and collected under the scope of the CODE (Clinical Outcomes in Digital Electrocardiology) study. The DNN outperform cardiology resident medical doctors in recognizing 6 types of abnormalities in 12-lead ECG recordings, with F1 scores above 80% and specificity over 99%. These results indicate ECG analysis based on DNNs, previously studied in a single-lead setup, generalizes well to 12-lead exams, taking the technology closer to the standard clinical practice.
226 citations
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TL;DR: An easy to use web-based software application that assembles the genomes of viruses quickly and accurately using a novel alignment method that constructs genomes by reference-based linking of de novo contigs by combining amino-acids and nucleotide scores.
Abstract: SUMMARY Genome Detective is an easy to use web-based software application that assembles the genomes of viruses quickly and accurately. The application uses a novel alignment method that constructs genomes by reference-based linking of de novo contigs by combining amino-acids and nucleotide scores. The software was optimized using synthetic datasets to represent the great diversity of virus genomes. The application was then validated with next generation sequencing data of hundreds of viruses. User time is minimal and it is limited to the time required to upload the data. AVAILABILITY AND IMPLEMENTATION Available online: http://www.genomedetective.com/app/typingtool/virus/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
226 citations
Authors
Showing all 42077 results
Name | H-index | Papers | Citations |
---|---|---|---|
Michael Marmot | 193 | 1147 | 170338 |
Pulickel M. Ajayan | 176 | 1223 | 136241 |
Alan D. Lopez | 172 | 863 | 259291 |
Jens Nielsen | 149 | 1752 | 104005 |
Mildred S. Dresselhaus | 136 | 762 | 112525 |
Jing Kong | 126 | 553 | 72354 |
Mauricio Terrones | 118 | 760 | 61202 |
Michael Brammer | 118 | 424 | 46763 |
Terence G. Langdon | 117 | 1158 | 61603 |
Caroline A. Sabin | 108 | 690 | 44233 |
Michael Brauer | 106 | 480 | 73664 |
Michael Bader | 103 | 735 | 37525 |
Michael S. Strano | 98 | 480 | 60141 |
Pablo Jarillo-Herrero | 91 | 245 | 39171 |
Riichiro Saito | 91 | 502 | 48869 |