Machine Learning Analysis of Arterial Oscillograms for Depression Level Diagnosis in Cardiovascular Health

Machine Learning Analysis of Arterial Oscillograms for Depression Level Diagnosis in Cardiovascular Health

The presented study explores the clustering of arterial oscillogram (AO) data among a sample of patients, focusing on ultra-low-frequency (ULF) indicators and their relationship with depression levels. Through dimensionality reduction using UMAP, two distinct classes emerged, categorized as lighter...

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Bibliographic Details
Main Authors: Vladislav Kaverinsky, Dmytro Vakulenko, Liudmyla Vakulenko, Kyrylo Malakhov
Format: Article
Language:English
Published: Riga Technical University Press 2024-10-01
Series:Complex Systems Informatics and Modeling Quarterly
Subjects:
machine learning
transdisciplinary research
data clustering
umap
arterial oscillogram
ulf
mental state diagnostic
Online Access:https://csimq-journals.rtu.lv/article/view/8982
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