Laura Bear
researcher
Facts
11 properties- Instance of
- human
- Occupation
- researcher
- Employer
- Bordeaux Segalen University
- Educated at
- University of Auckland[2]
- Doctoral advisor
- Leo K Cheng, Bruce Smaill[3][4]
- Academic degree
- Doctor of Philosophy[6]
- Academic thesis
- A Comprehensive Evaluation of Cardiac Electro-Anatomic Mapping Using Body Surface Potentials[9]
- On focus list of Wikimedia project
- NZThesisProject[10]
🏷️ Also known as
en Laura Bear
🔖 Identifiers · 7
- ORCID iD
- 0000-0002-7070-2492
- VIAF cluster ID
- 99166002494375022157
- OpenAlex ID
- A5077408770
- Google Scholar author ID
- DyWR868AAAAJ
- IdRef ID
- 262388553
- ResearchGate profile ID
- Laura_Bear
- Scopus author ID
- 57069974000
🔗 Connections
Author of 7
Cardiac Propagation Pattern Mapping With Vector Field for Helping Tachyarrhythmias Diagnosis With Clinical Tridimensional Electro-Anatomical Mapping Tools,
Effects of ECG Signal Processing on the Inverse Problem of Electrocardiography,
Evaluation of Fifteen Algorithms for the Resolution of the Electrocardiography Imaging Inverse Problem Using ex-vivo and in-silico Data,
Reduction of Effects of Noise on the Inverse Problem of Electrocardiography With Bayesian Estimation,
Solving Inverse Electrocardiographic Mapping Using Machine Learning and Deep Learning Frameworks,
Spatiotemporal approximation of cardiac activation and recovery isochrones,
The effect of interpolating low amplitude leads on the inverse reconstruction of cardiac electrical activity
← Authored by 7
Cardiac Propagation Pattern Mapping With Vector Field for Helping Tachyarrhythmias Diagnosis With Clinical Tridimensional Electro-Anatomical Mapping Tools,
Effects of ECG Signal Processing on the Inverse Problem of Electrocardiography,
Evaluation of Fifteen Algorithms for the Resolution of the Electrocardiography Imaging Inverse Problem Using ex-vivo and in-silico Data,
Reduction of Effects of Noise on the Inverse Problem of Electrocardiography With Bayesian Estimation,
Solving Inverse Electrocardiographic Mapping Using Machine Learning and Deep Learning Frameworks,
Spatiotemporal approximation of cardiac activation and recovery isochrones,
The effect of interpolating low amplitude leads on the inverse reconstruction of cardiac electrical activity
Press Enter · cited answer in seconds