Separation of murmur, normal, and poor signal quality signals using HSMM confidences.

Separation of murmur, normal, and poor signal quality signals using HSMM confidences.

<p>The difference between the normal HSMM confidence, <i>C</i><sup>(<i>N</i>)</sup>, and the most confident murmur HSMM, <i>C</i><sup>(<i>M</i>)</sup>, is used to predict murmur likelihood <i>C</i><sup>(&...

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Bibliographic Details
Main Author: Andrew McDonald (2307400) (author)
Other Authors: Mark J. F. Gales (20323754) (author), Anurag Agarwal (516905) (author)
Published: 2024
Subjects:
Cell Biology
Molecular Biology
Biotechnology
Cancer
Space Science
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
representative clinical datasets
recurrent neural network
provide interpretable predictions
new test data
machine learning analysis
existing approaches require
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many previous algorithms
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individual sound components
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detect heart murmurs
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markov model
many end
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expected sound
challenge tasks
heart murmur
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stage algorithm
significantly alter
segmentation errors
s2 sounds
resource environments
properties make
promising tool
performance exceeded
improve upon
hidden semi
find s1
algorithm formed
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