One Hundred Years of Hypertension Research: Topic Modeling Study.

ABSTRACT:

Background

Due to scientific and technical advancements in the field, published hypertension research has developed substantially during the last decade. Given the amount of scientific material published in this field, identifying the relevant information is difficult. We used topic modeling, which is a strong approach for extracting useful information from enormous amounts of unstructured text.

Objective

This study aims to use a machine learning algorithm to uncover hidden topics and subtopics from 100 years of peer-reviewed hypertension publications and identify temporal trends.

Methods

The titles and abstracts of hypertension papers indexed in PubMed were examined. We used the latent Dirichlet allocation model to select 20 primary subjects and then ran a trend anal

SUBMITTER: Abba M 

PROVIDER: S-EPMC9161044 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature