An early detection and diagnosis of atrial fibrillation sets the course for timely intervention to prevent potentially occurring comorbidities. Electrocardiogram data resulting from electrophysiological cohort modeling and simulation can be a valuable data resource for improving automated atrial fibrillation risk stratification with machine learning techniques and thus, reduces the risk of stroke in affected patients.
Umfang: XII, 252 S.
Preis: 49.00 €
These are words or phrases in the text that have been
automatically identified by the
Named Entity Recognition and Disambiguation service,
which provides Wikipedia
()
and Wikidata
(
)
links for these entities.
Nagel, C. 2023. Multiscale Cohort Modeling of Atrial Electrophysiology : Risk Stratification for Atrial Fibrillation through Machine Learning on Electrocardiograms. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000155927
Dieses Buch ist lizenziert unter Creative Commons Attribution + ShareAlike 4.0
Dieses Buch ist Peer reviewed. Informationen dazu finden Sie hier
Veröffentlicht am 24. April 2023
Englisch
280
Paperback | 978-3-7315-1281-3 |