Rob MacLeod

Professor

University of Utah

United States

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About

Rob MacLeod is a Professor at the University of Utah, United States. His research focuses on the application of uncertainty quantification in myocardial fiber orientation and cardiac activation patterns, as well as the functional and structural abnormalities associated with atrial fibrillation. He has contributed to advancements in machine learning techniques for electrogram classification and investigates the impact of structural remodeling on arrhythmogenesis in various cardiac models.

Articles (20)

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2025

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2020

Collaborators (10)

Sumientra Rampersad

Assistant Professor

University of Massachusetts Boston

UNITED STATES

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Matthias Schaufelberger

GERMANY

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Wilson W. Good

UNITED STATES

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Oleg Aslanidi

Reader

King’s College London

UNITED KINGDOM

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Linwei Wang

UNITED STATES

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Xiajun Jiang

Assistant professor

Rowan University

UNITED STATES

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Gernot Plank

Medical University of Graz

AUSTRIA

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Marta Varela

Imperial College London

UNITED KINGDOM

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Matthijs Cluitmans

University of Maastricht

NETHERLANDS

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Jaume Coll-Font

UNITED STATES

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Rob MacLeod

Research Interests

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About

Articles (20)

Uncertainty quantification via polynomial chaos expansion of myocardial fibre orientation and cardiac activation patterns

Uncertainty quantification via polynomial chaos expansion of myocardial fibre orientation and cardiac activation patterns

Diffuse functional and structural abnormalities in fibrosis: Potential structural basis for sustaining atrial fibrillation

Contrastive pretraining improves deep learning classification of endocardial electrograms in a preclinical model

Effective ablation settings that predict chronic scar after atrial ablation with HELIOSTAR™ multi-electrode radiofrequency balloon catheter

Functional and Structural Remodeling as Atrial Fibrillation Progresses in a Persistent Atrial Fibrillation Canine Model

Image quality assessment and automation in late gadolinium-enhanced MRI of the left atrium in atrial fibrillation patients

PO-05-070 MAPPING IN-VIVO ELECTROGRAMS TO FIBROSIS IN ATRIAL FIBRILLATION USING MACHINE LEARNING

PO-05-145 HETEROGENEOUS FIBROTIC ARCHITECTURE INFLUENCES ATRIAL FIBRILLATION (AF) INDUCIBILITY: INSIGHTS FROM A TRANSGENIC GOAT MODEL

PO-FP-008 RADIATION-INDUCED STRUCTURAL REMODELING IN HEALTHY MYOCARDIUM: INSIGHTS FROM CMRI

Improving Generalization by Learning Geometry-Dependent and Physics-Based Reconstruction of Image Sequences

UncertainSCI: Uncertainty quantification for computational models in biomedicine and bioengineering

Reducing Line-of-Block Artifacts in Cardiac Activation Maps Estimated Using ECG Imaging: A Comparison of Source Models and Estimation Methods

Reconstruction of cardiac position using body surface potentials

Combining endocardial mapping and electrocardiographic imaging (ECGI) for improving PVC localization: A feasibility study

Estimation and Validation of Cardiac Conduction Velocity and Wavefront Reconstruction Using Epicardial and Volumetric Data

The effect of interpolating low amplitude leads on the inverse reconstruction of cardiac electrical activity

The Impact of Torso Signal Processing on Noninvasive Electrocardiographic Imaging Reconstructions

Identifying locations of re-entrant drivers from patient-specific distribution of fibrosis in the left atrium

Novel experimental model for studying the spatiotemporal electrical signature of acute myocardial ischemia: a translational platform

Collaborators (10)

Sumientra Rampersad

Matthias Schaufelberger

Wilson W. Good

Oleg Aslanidi

Linwei Wang

Xiajun Jiang

Gernot Plank

Marta Varela

Matthijs Cluitmans

Jaume Coll-Font

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