Learning Structural Knowledge from the ECG

Learning Structural Knowledge from the ECG

We tackle the problem of discovering, without the “manual” aid of an expert, implicit relations and temporal constraints from a collection of dated events detected on temporally structured signals. The approach associates tightly signal processing and symbolic learning methods. It is illustrated on...

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Hauptverfasser: Wang, F., Quiniou, R., Carrault, G., Cordier, M. -O.
Format: Buchkapitel
Sprache:eng
Schlagworte:
Biological and medical sciences
Implicit Relation
Inductive Logic Programming
Medical sciences
Probabilistic Neural Network
Symbolic Event
Temporal Constraint
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container_volume 2199
creator Wang, F.
Quiniou, R.
Carrault, G.
Cordier, M. -O.
description We tackle the problem of discovering, without the “manual” aid of an expert, implicit relations and temporal constraints from a collection of dated events detected on temporally structured signals. The approach associates tightly signal processing and symbolic learning methods. It is illustrated on learning cardiac arrhythmias from ECGs.
doi_str_mv 10.1007/3-540-45497-7_44
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identifier ISSN: 0302-9743
ispartof Lecture notes in computer science, 2001, Vol.2199, p.288-294
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1611-3349
language eng
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source Springer Books
subjects Biological and medical sciences
Implicit Relation
Inductive Logic Programming
Medical sciences
Probabilistic Neural Network
Symbolic Event
Temporal Constraint
title Learning Structural Knowledge from the ECG
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