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A prediction tool for plaque progression based on patient-specific multi-physical modeling.

, , , , , , and . PLoS Comput. Biol., (2021)

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Convolutional neural network based automatic plaque characterization from intracoronary optical coherence tomography images., , , , , , and . CoRR, (2018)Correction: A prediction tool for plaque progression based on patient-specific multi-physical modeling., , , , , , and . PLoS Comput. Biol., (2021)A prediction tool for plaque progression based on patient-specific multi-physical modeling., , , , , , and . PLoS Comput. Biol., (2021)Redundancy and Novelty Between ECG Leads Based on Linear Correlation., , , , , and . BIOSIGNALS, page 359-365. SCITEPRESS, (2023)Morphological and Stress Vulnerability Indices for Human Coronary Plaques and Their Correlations with Cap Thickness and Lipid Percent: An IVUS-Based Fluid-Structure Interaction Multi-patient Study., , , , , , , , , and . PLoS Comput. Biol., (2015)12-Lead ECG Reconstruction via Combinatoric Inclusion of Fewer Standard ECG Leads with Implications for Lead Information and Significance., , , , , and . BIOSIGNALS, page 133-141. SCITEPRESS, (2022)Convolutional neural network based automatic plaque characterization for intracoronary optical coherence tomography images., , , , , , and . Medical Imaging: Image Processing, volume 10574 of SPIE Proceedings, page 1057432. SPIE, (2018)