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Supplementary material

Year: 2025

Type: supplementary-materials

Abstract: Supplementary material to publication Quantifying Cardiovascular Autonomic Aging with Machine Learning

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17353168

Author: Schumann, Andy

Language: English

Topic: Heart Rate Variability and Autonomic Control

Subfield: Cardiology and Cardiovascular Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W7090815363

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