Shaheim Ogbomo-Harmitt

Orcid: 0000-0002-9547-4828

According to our database1, Shaheim Ogbomo-Harmitt authored at least 10 papers between 2022 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
Towards Deep Learning Surrogate for the Forward Problem in Electrocardiology: A Scalable Alternative to Physics-Based Models.
CoRR, December, 2025

Machine Learning Highlights Left Atrial Fibrotic Heterogeneity as a Key Predictor of Atrial Fibrillation Inducibility.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers, 2025

Enhanced Stroke Risk Stratification of Atrial Fibrillation Patients Using Explainable Machine Learning.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers, 2025

2024
An investigation into the causes of race bias in AI-based cine CMR segmentation.
CoRR, 2024

Rotor Core Projection Ablation (RCPA): Novel Computational Approach to Catheter Ablation Therapy for Atrial Fibrillation.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Workshop, 2024

2023
Effects of Fibrotic Border Zone on Drivers for Atrial Fibrillation: An In-Silico Mechanistic Investigation.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers, 2023

Modelling Blood Flow and Biochemical Reactions Underlying Thrombogenesis in Atrial Fibrillation.
Proceedings of the Functional Imaging and Modeling of the Heart, 2023

2022
TESSLA: Two-Stage Ensemble Scar Segmentation for the Left Atrium.
Proceedings of the Left Atrial and Scar Quantification and Segmentation - First Challenge, 2022

Impact of Fibrosis Border Zone Characterisation on Fibrosis-Substrate Isolation Ablation Outcome for Atrial Fibrillation.
Proceedings of the Computing in Cardiology, 2022

Physics-Informed Fully Connected and Recurrent Neural Networks for Cardiac Electrophysiology Modelling.
Proceedings of the Computing in Cardiology, 2022


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