TY  - JOUR
A1  - Werfel, Stanislas
A1  - Günthner, Roman
A1  - Hapfelmeier, Alexander
A1  - Hanssen, Henner
A1  - Kotliar, Konstantin
A1  - Heemann, Uwe
A1  - Schmaderer, Christoph
A2  - Guzik, Tomasz J.
T1  - Identification of cardiovascular high-risk groups from dynamic retinal vessel signals using untargeted machine learning
T2  - Cardiovascular Research
N2  - Dynamic retinal vessel analysis (DVA) provides a non-invasive way to assess microvascular function in patients and potentially to improve predictions of individual cardiovascular (CV) risk. The aim of our study was to use untargeted machine learning on DVA in order to improve CV mortality prediction and identify corresponding response alterations.
KW  - Machine learning
KW  - Retinal vessels
KW  - Microcirculation
KW  - Haemodialysis
KW  - Myocardial infarction and cardiac death
Y1  - 2022
UR  - https://opus.bibliothek.fh-aachen.de/opus4/frontdoor/index/index/docId/9792
SN  - 0008-6363
VL  - 118
IS  - 2
SP  - 612
EP  - 621
PB  - Oxford University Press
CY  - Oxford
ER  -