Browse by UCL people
Group by: Type | Date
Number of items: 7.
Article
Ledezma, CA;
Zhou, X;
Rodríguez, B;
Tan, PJ;
Díaz-Zuccarini, V;
(2019)
A modeling and machine learning approach to ECG feature engineering for the detection of ischemia using pseudo-ECG.
PLoS One
, 14
(8)
, Article e0220294. 10.1371/journal.pone.0220294.
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Ledezma Rondon, CA;
Kappler, B;
Meijborg, V;
Boukens, B;
Stijnen, M;
Tan, PJ;
Diaz, V;
(2018)
Bridging Organ- and Cellular-Level Behavior in Ex Vivo Experimental Platforms Using Populations of Models of Cardiac Electrophysiology.
Journal of Engineering and Science in Medical Diagnostics and Therapy
, 1
(4)
, Article 041003. 10.1115/1.4040589.
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Proceedings paper
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Ledezma, CA;
Kappler, B;
Meijborg, V;
Boukens, B;
Stijnen, M;
Tan, PJ;
Diaz, V;
(2017)
A big data approach to myocyte membrane analysis: using populations of models to understand the cellular causes of heart failure.
In:
Proceedings of Computing in Cardiology 2017.
Computing in Cardiology 2017: Rennes, France.
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Ledezma, CA;
Kappler, B;
Meijborg, V;
Boukens, B;
Stijnen, M;
Tan, PJ;
Diaz, V;
(2017)
Evaluating the risks of arrhythmia through big data: automatic processing and neural networks to classify epicardial electrograms.
In:
Proceedings of Computing in Cardiology 2017.
Computing in Cardiology: Rennes, France.
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Ledezma, CA;
Perpinan, G;
Severeyn, E;
Altuve, M;
(2015)
Data Fusion for QRS Complex Detection in Multi-Lead Electrocardiogram Recordings.
In: Romero, E and Lepore, N and GarciaArteaga, JD and Brieva, J, (eds.)
Proceedings of SPIE Volume 9681, 11th International Symposium on Medical Information Processing and Analysis.
SPIE: Cuenca, Ecuador.
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Ledezma Rondon, CA;
Kappler, B;
Meijborg, V;
Boukens, B;
Stijnen, M;
Tan, PJ;
Diaz, V;
(2017)
Using populations of models to navigate big data in electrophysiology: evaluation of parameter sensitivity of action potential models.
In:
Proceedings of Computing in Cardiology 2017.
Computing in Cardiology 2017: Rennes, France.
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Thesis
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Ledezma Rondon, Carlos Alberto;
(2020)
Populations of models and machine learning for the assessment of cardiac electrophysiology.
Doctoral thesis (Ph.D), UCL (University College London).
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