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-Juergen Bär

Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Jena, Germany. · pubmed

Paper

Abstract

Machine learning has become an important tool in precision medicine and aging research. We introduce the

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Research summary

The paper claims to quantify cardiovascular autonomic aging using machine learning techniques. This research is relevant as it addresses the mechanisms of aging and seeks to understand cardiovascular aging, which is a significant aspect of longevity and age-related health.

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