Can machine learning improve patient selection for cardiac resynchronization therapy?
Rationale Multiple clinical trials support the effectiveness of cardiac resynchronization therapy (CRT); however, optimal patient selection remains challenging due to substantial treatment heterogeneity among patients who meet the clinical practice guidelines. Objective To apply machine learning to...
Main Authors: | Santus, Enrico (Author), Forsyth, Alexander W. (Author), Haimson, Josh (Author), Barzilay, Regina (Author) |
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Other Authors: | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor) |
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS),
2020-04-01T11:48:27Z.
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Subjects: | |
Online Access: | Get fulltext |
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