American journal of physiology. Heart and circulatory physiologyHumansMachine LearningAgingAutonomic Nervous SystemMale
Quantifying cardiovascular autonomic aging with machine learning.
Andy Schumann, Yubraj Gupta, Maria Geisler, Feliberto de la Cruz, Denis Gerstorf, Ilja Demuth, Maja Olecka, Christian Gaser, Karl-Jürgen Bär
Published: 202510.1152/ajpheart.00693.2025
Abstract
Machine learning has become an important tool in precision medicine and aging research. We introduce the cardiovascular autonomic age (CAA) gap, a novel metric quantifying the deviation between machine learning-estimated biological age and chronologi…
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