ArticleJournal of clinical hypertension (Greenwich, Conn.)2025
Research on Prediction model of Carotid-Femoral Pulse Wave Velocity: Based on Machine Learning Algorithm.
Article in Journal of clinical hypertension (Greenwich, Conn.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Machine Learning Prediction Model for Carotid-Femoral Pulse Wave Velocity in Cardiovascular Health Assessments.Journal of clinical hypertension (Greenwich, Conn.) · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
Carotid-femoral pulse wave velocity (cf-PWV) is an important but difficult to obtain measure of arterial stiffness and an independent predictor of cardiovascular events and all-cause mortality. The objective of this study was to develop a predictive model for cf-PWV based on brachial-ankle pulse wave velocity (baPWV) and other the accessible clinical parameters. This model aims to allow patients to estimate their cf-PWV in advance without the need for direct measurement. We selected participants of the Northern Shanghai community from 2013 to 2022 as the study object. The Pearson correlation coefficient was employed for correlation analysis in feature selection. The linear regression models demonstrated low root mean square error (RMSE), error term (ε), and R
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