A Data Analytics Approach for Revealing Influencing Factors of HPV-Related Cancers From Population-Level Statistics Data

Human papillomavirus (HPV) is considered as one of the major causes of multiple cancers, including cervical, anal, and vaginal cancers. Some studies analyzed the infection patterns of cancers caused by HPV using individual clinical test data, which is resource and time expensive. In order to facilit...

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Autores principales: Xiaoqin Du, Qi Tan
Formato: article
Lenguaje:EN
Publicado: Frontiers Media S.A. 2021
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Acceso en línea:https://doaj.org/article/788cc8e5490149c68cd96e79a6cddf92
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spelling oai:doaj.org-article:788cc8e5490149c68cd96e79a6cddf922021-12-02T09:26:00ZA Data Analytics Approach for Revealing Influencing Factors of HPV-Related Cancers From Population-Level Statistics Data2296-424X10.3389/fphy.2021.789938https://doaj.org/article/788cc8e5490149c68cd96e79a6cddf922021-12-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fphy.2021.789938/fullhttps://doaj.org/toc/2296-424XHuman papillomavirus (HPV) is considered as one of the major causes of multiple cancers, including cervical, anal, and vaginal cancers. Some studies analyzed the infection patterns of cancers caused by HPV using individual clinical test data, which is resource and time expensive. In order to facilitate the understanding of cancers caused by HPV, we propose to use data analytics methods to reveal the influencing factors from the population-level statistics data, which is available more easily. Particularly, we demonstrate the effectiveness of data analytics approach by introducing a predictive analytics method in studying the risk factors of cervix cancer in the United States. Besides accurate prediction of the number of infections, the predictive analytics method discovers the population statistic factors that most affect the cervical cancer infection pattern. Furthermore, we discuss the potential directions in developing more advanced data analytics approaches in studying cancers caused by HPV.Xiaoqin DuQi TanFrontiers Media S.A.articledata analytics approachHPV-related cancerpopulation-level statistics dataregression modelHPV—human papillomavirusPhysicsQC1-999ENFrontiers in Physics, Vol 9 (2021)
institution DOAJ
collection DOAJ
language EN
topic data analytics approach
HPV-related cancer
population-level statistics data
regression model
HPV—human papillomavirus
Physics
QC1-999
spellingShingle data analytics approach
HPV-related cancer
population-level statistics data
regression model
HPV—human papillomavirus
Physics
QC1-999
Xiaoqin Du
Qi Tan
A Data Analytics Approach for Revealing Influencing Factors of HPV-Related Cancers From Population-Level Statistics Data
description Human papillomavirus (HPV) is considered as one of the major causes of multiple cancers, including cervical, anal, and vaginal cancers. Some studies analyzed the infection patterns of cancers caused by HPV using individual clinical test data, which is resource and time expensive. In order to facilitate the understanding of cancers caused by HPV, we propose to use data analytics methods to reveal the influencing factors from the population-level statistics data, which is available more easily. Particularly, we demonstrate the effectiveness of data analytics approach by introducing a predictive analytics method in studying the risk factors of cervix cancer in the United States. Besides accurate prediction of the number of infections, the predictive analytics method discovers the population statistic factors that most affect the cervical cancer infection pattern. Furthermore, we discuss the potential directions in developing more advanced data analytics approaches in studying cancers caused by HPV.
format article
author Xiaoqin Du
Qi Tan
author_facet Xiaoqin Du
Qi Tan
author_sort Xiaoqin Du
title A Data Analytics Approach for Revealing Influencing Factors of HPV-Related Cancers From Population-Level Statistics Data
title_short A Data Analytics Approach for Revealing Influencing Factors of HPV-Related Cancers From Population-Level Statistics Data
title_full A Data Analytics Approach for Revealing Influencing Factors of HPV-Related Cancers From Population-Level Statistics Data
title_fullStr A Data Analytics Approach for Revealing Influencing Factors of HPV-Related Cancers From Population-Level Statistics Data
title_full_unstemmed A Data Analytics Approach for Revealing Influencing Factors of HPV-Related Cancers From Population-Level Statistics Data
title_sort data analytics approach for revealing influencing factors of hpv-related cancers from population-level statistics data
publisher Frontiers Media S.A.
publishDate 2021
url https://doaj.org/article/788cc8e5490149c68cd96e79a6cddf92
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