About: Classification of pediatric pneumonia using chest X-rays by functional regression

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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	Classification of pediatric pneumonia using chest X-rays by functional regression
Creator	Islam, Nazmul
source	ArXiv
abstract	An accurate and prompt diagnosis of pediatric pneumonia is imperative for successful treatment intervention. One approach to diagnose pneumonia cases is using radiographic data. In this article, we propose a novel parsimonious scalar-on-image classification model adopting the ideas of functional data analysis. Our main idea is to treat images as functional measurements and exploit underlying covariance structures to select basis functions; these bases are then used in approximating both image profiles and corresponding regression coefficient. We re-express the regression model into a standard generalized linear model where the functional principal component scores are treated as covariates. We apply the method to (1) classify pneumonia against healthy and viral against bacterial pneumonia patients, and (2) test the null effect about the association between images and responses. Extensive simulation studies show excellent numerical performance in terms of classification, hypothesis testing, and efficient computation.
has issue date	2020-05-07(xsd:dateTime)
has license	arxiv
sha1sum (hex)	99c08cbf550b62bc3905d9125a40bbed7e85c04e
resource representing a document's title	Classification of pediatric pneumonia using chest X-rays by functional regression
resource representing a document's body	covid:99c08cbf550b62bc3905d9125a40bbed7e85c04e#body_text
is schema:about of	named entity 'pneumonia' named entity 'structures' named entity 'diagnosis' named entity 'Classification' named entity 'PRINCIPAL COMPONENT' »more»

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