Machine Learning prediction of cardiac resynchronisation therapy response from combination of clinic...
Machine Learning prediction of cardiac resynchronisation therapy response from combination of clinical and model-driven data
About this item
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Publisher
Cold Spring Harbor: Cold Spring Harbor Laboratory Press
Journal title
Language
English
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Publisher
Cold Spring Harbor: Cold Spring Harbor Laboratory Press
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Contents
Background: Up to 30%-50% of chronic heart failure patients who underwent cardiac resynchronization therapy (CRT) do not respond to the treatment. Therefore, patient stratification for CRT and optimization of CRT device settings remain a challenge. Objective: The main goal of our study is to develop a predictive model of CRT outcome using a combina...
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Full title
Machine Learning prediction of cardiac resynchronisation therapy response from combination of clinical and model-driven data
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TN_cdi_proquest_journals_2569491418
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2569491418
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E-ISSN
2692-8205
DOI
10.1101/2021.09.03.458464
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https://www.proquest.com/docview/2569491418?pq-origsite=primo&accountid=13902
