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DIA-PINN. A physics-informed machine learning method to estimate global intrinsic diastolic chamber properties of the left ventricle from pressure-volume data
2026-03-06
cardiovascular medicine
Title + abstract only
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Background: Pressure volume (PV) loop analysis remains the gold standard for assessing the intrinsic global diastolic properties of the left ventricle (LV). Traditional fitting techniques rely on local, phase-constrained fittings and are limited due to their sensitivity to noise, landmark selection, violation of assumptions, and non-convergence. Objective: To develop and validate DIAPINN, a physics-informed neural network (PINN) framework capable of calculating intrinsic diastolic properties of ...
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