Pulse wave time series unsupervised clustering with importance ratios for heart failure subgroups detection

Pulse wave time series unsupervised clustering with importance ratios for heart failure subgroups detection

Heart failure (HF) is a significant global public health issue, and accurate diagnosis and effective management are crucial for improving patient outcomes. This study aims to identify potential HF patient subgroups based on the pulse wave time series via unsupervised clustering algorithms and to qua...

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Bibliographic Details
Main Authors: Dandan WU, Ryohei ONO, Sirui WANG, Yoshio KOBAYASHI, Hao LIU
Format: Article
Language:English
Published: The Japan Society of Mechanical Engineers 2024-12-01
Series:Journal of Biomechanical Science and Engineering
Subjects:
pulse wave
heart failure
unsupervised clustering
k-means++
random forest classifier
importance ratio
Online Access:https://www.jstage.jst.go.jp/article/jbse/20/2/20_24-00325/_pdf/-char/en
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https://www.jstage.jst.go.jp/article/jbse/20/2/20_24-00325/_pdf/-char/en

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