Cargando…

Identifying Topics and Evolutionary Trends of Literature on Brain Metastases Using Latent Dirichlet Allocation

Research on brain metastases kept innovating. We aimed to illustrate what topics the research focused on and how it varied in different periods of all the studies on brain metastases with topic modelling. We used the latent Dirichlet allocation model to analyse the titles and abstracts of 50,176 art...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Jiarong, Williams, Matt, Huang, Yanming, Si, Shijing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9201447/
https://www.ncbi.nlm.nih.gov/pubmed/35720132
http://dx.doi.org/10.3389/fmolb.2022.858577
_version_ 1784728323650224128
author Chen, Jiarong
Williams, Matt
Huang, Yanming
Si, Shijing
author_facet Chen, Jiarong
Williams, Matt
Huang, Yanming
Si, Shijing
author_sort Chen, Jiarong
collection PubMed
description Research on brain metastases kept innovating. We aimed to illustrate what topics the research focused on and how it varied in different periods of all the studies on brain metastases with topic modelling. We used the latent Dirichlet allocation model to analyse the titles and abstracts of 50,176 articles on brain metastases retrieved from Web of Science, Embase and MEDLINE. We further stratified the articles to find out the topic trends of different periods. Our study identified that a rising number of studies on brain metastases were published in recent decades at a higher rate than all cancer articles. Overall, the major themes focused on treatment and histopathology. Radiotherapy took over the first and third places in the top 20 topics. Since the 2010’s, increasing attention concerned about gene mutations. Targeted therapy was a popular topic of brain metastases research after 2020.
format Online
Article
Text
id pubmed-9201447
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-92014472022-06-17 Identifying Topics and Evolutionary Trends of Literature on Brain Metastases Using Latent Dirichlet Allocation Chen, Jiarong Williams, Matt Huang, Yanming Si, Shijing Front Mol Biosci Molecular Biosciences Research on brain metastases kept innovating. We aimed to illustrate what topics the research focused on and how it varied in different periods of all the studies on brain metastases with topic modelling. We used the latent Dirichlet allocation model to analyse the titles and abstracts of 50,176 articles on brain metastases retrieved from Web of Science, Embase and MEDLINE. We further stratified the articles to find out the topic trends of different periods. Our study identified that a rising number of studies on brain metastases were published in recent decades at a higher rate than all cancer articles. Overall, the major themes focused on treatment and histopathology. Radiotherapy took over the first and third places in the top 20 topics. Since the 2010’s, increasing attention concerned about gene mutations. Targeted therapy was a popular topic of brain metastases research after 2020. Frontiers Media S.A. 2022-06-02 /pmc/articles/PMC9201447/ /pubmed/35720132 http://dx.doi.org/10.3389/fmolb.2022.858577 Text en Copyright © 2022 Chen, Williams, Huang and Si. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Molecular Biosciences
Chen, Jiarong
Williams, Matt
Huang, Yanming
Si, Shijing
Identifying Topics and Evolutionary Trends of Literature on Brain Metastases Using Latent Dirichlet Allocation
title Identifying Topics and Evolutionary Trends of Literature on Brain Metastases Using Latent Dirichlet Allocation
title_full Identifying Topics and Evolutionary Trends of Literature on Brain Metastases Using Latent Dirichlet Allocation
title_fullStr Identifying Topics and Evolutionary Trends of Literature on Brain Metastases Using Latent Dirichlet Allocation
title_full_unstemmed Identifying Topics and Evolutionary Trends of Literature on Brain Metastases Using Latent Dirichlet Allocation
title_short Identifying Topics and Evolutionary Trends of Literature on Brain Metastases Using Latent Dirichlet Allocation
title_sort identifying topics and evolutionary trends of literature on brain metastases using latent dirichlet allocation
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9201447/
https://www.ncbi.nlm.nih.gov/pubmed/35720132
http://dx.doi.org/10.3389/fmolb.2022.858577
work_keys_str_mv AT chenjiarong identifyingtopicsandevolutionarytrendsofliteratureonbrainmetastasesusinglatentdirichletallocation
AT williamsmatt identifyingtopicsandevolutionarytrendsofliteratureonbrainmetastasesusinglatentdirichletallocation
AT huangyanming identifyingtopicsandevolutionarytrendsofliteratureonbrainmetastasesusinglatentdirichletallocation
AT sishijing identifyingtopicsandevolutionarytrendsofliteratureonbrainmetastasesusinglatentdirichletallocation