AIMC Topic: Long QT Syndrome

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Emerging Concepts and Applied Machine Learning Research in Patients with Drug-Induced Repolarization Disorders.

Studies in health technology and informatics Jun 16, 2020
The paper presents a review of current research to develop predictive models for automated detection of drug-induced repolarization disorders and shows a feasibility study for developing machine learning tools trained on massive multimodal datasets o...
Humans Machine Learning Electrocardiography Long QT Syndrome Death, Sudden, Cardiac Torsades de Pointes
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Support vector machine-based assessment of the T-wave morphology improves long QT syndrome diagnosis.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology Nov 1, 2018
AIMS: Diagnosing long QT syndrome (LQTS) is challenging due to a considerable overlap of the QTc-interval between LQTS patients and healthy controls. The aim of this study was to investigate the added value of T-wave morphology markers obtained from ...
Humans Phenotype Retrospective Studies Reproducibility of Results Risk Factors Time Factors Genetic Predisposition to Disease Electrocardiography Support Vector Machine Action Potentials Predictive Value of Tests Signal Processing, Computer-Assisted Long QT Syndrome Heart Conduction System Heart Rate
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