Ana Mincholé Lapuente
Ana Mincholé graduated in Physics from the University of Zaragoza, Spain in 2002. She also obtained an MSc with distinction at Chalmers University of Technology, Gothenburg, Sweden, in the MSc program “Nanoscale Physics and Engineering”. She then started a PhD in Biomedical Engineering at the Communication Technology Group at the University of Zaragoza, Spain supervised by Prof. Pablo Laguna. Her PhD focused on the analysis of the electrocardiographic signal and the development of novel ECG biomarkers for the stratification of arrhythmic risk. During her PhD, she conducted research visits to the Laboratory for Biomedical Computer Systems and Imaging at the University of Ljubljana, Slovenia, with Prof. Franc Jager, and to the Argentinian Institute of Mathematics, CONICET with Dr Pedro Arini and Dr Marcelo Risk. After her PhD and a short postdoc experience in the European preDiCt project at the University of Oxford, she was awarded a Marie Curie Intra-European Fellowship for Career Development and joined Prof. Blanca Rodriguez’ group at the Department of Computer Science at the University of Oxford, UK. After the fellowship, she continued working at the University of Oxford holding the position of Senior Research Associate until 2019. Then, she moved to the University of Zaragoza to join the Multiscale in Mechanical and Biological Engineering group within the European PRIMAGE project where she applied her expertise in multiscale modelling and simulation and high-performance computing to model tumour growth. In 2020, she was awarded a Ramón y Cajal Senior Research Fellowship from the Spanish Ministry of Science and Innovation and joined the Biomedical Signal Interpretation and Computational Simulation (BSICoS) group at the University of Zaragoza in 2021.
Her research interests include the development and evaluation of synergistic data-driven approaches where modelling and simulation are used to integrate biomedical data at different scales in the investigation of cardiac pathological conditions. This is in line with her expertise in the combination of computational modelling and simulation of physiological processes, biomedical signal analysis and machine learning techniques to stratify risk either drug-induced or due to pathological conditions.
Assessment and optimization of conduction system pacing for anti-bradycardia pacemaker therapy Conferencia
STAFF-MALT Symposium 2022, Senohraby, Czech Republic, 2022.
Comparación de los efectos de la estimulación cardíaca convencional y la estimulación de rama izquierda sobre la despolarización y repolarización ventricular en el ECG Conferencia
Jornadas de Jóvenes Investigadores del I3A, Zaragoza, España, 2022.
Right Ventricular vs Left Bundle Branch Pacing-Induced Changes in ECG Depolarization and Repolarization Conferencia
Proceedings of the XLVIII International Conference on Computing in Cardiology, Tampere, Finland, 2022.
Changes in QRS and T-wave Loops Subsequent to an Increase in Left Ventricle Globularity as in Intrauterine Growth Restriction: a Simulation Study Conferencia
Proceedings of the XLVII International Conference on Computing in Cardiology, Rimini, Italy, 2020.
Artículos de revista
Distinct ECG phenotypes identified in hypertrophic cardiomyopathy using machine learning associate with arrhythmic risk markers Artículo de revista
En: Frontiers in Physiology, vol. 9, no. 213, pp. 1-13, 2018.
Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances Artículo de revista
En: Journal of the Royal Society: Interface, vol. 15, 2018.
Artículos de revista
Sudden cardiac death and pump failure death prediction in chronic heart failure by combining ECG and clinical markers in an integrated risk model Artículo de revista
En: PLOS ONE, vol. 12, no. 10: e0186152, pp. 1-15, 2017.
T-wave Morphology Restitution Predicts Sudden Cardiac Death in Patients with Chronic Heart Failure Artículo de revista
En: Journal of the American Heart Association, no. 6: e005310, pp. 1-12, 2017.