About: Deep Learning for Automatic Pneumonia Detection

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Deep Learning for Automatic Pneumonia Detection
Creator	Gabruseva, Tatiana Kalinin, Alexandr Poplavskiy, Dmytro
source	ArXiv
abstract	Pneumonia is the leading cause of death among young children and one of the top mortality causes worldwide. The pneumonia detection is usually performed through examine of chest X-ray radiograph by highly-trained specialists. This process is tedious and often leads to a disagreement between radiologists. Computer-aided diagnosis systems showed the potential for improving diagnostic accuracy. In this work, we develop the computational approach for pneumonia regions detection based on single-shot detectors, squeeze-and-excitation deep convolution neural networks, augmentations and multi-task learning. The proposed approach was evaluated in the context of the Radiological Society of North America Pneumonia Detection Challenge, achieving one of the best results in the challenge.
has issue date	2020-05-28(xsd:dateTime)
has license	arxiv
sha1sum (hex)	f76dea0783a05649e4a7f77bf914b0f39a4f14fe
resource representing a document's title	Deep Learning for Automatic Pneumonia Detection
resource representing a document's body	covid:f76dea0783a05649e4a7f77bf914b0f39a4f14fe#body_text
is schema:about of	named entity 'NORTH AMERICA' named entity 'CAUSES' named entity 'LEADS' named entity 'PNEUMONIA' named entity 'YOUNG CHILDREN' »more»

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