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Esophageal virtual disease landscape using mechanics-informed machine learning
In this work, we present a hybrid framework that combines fluid mechanics and machine learning to identify the underlying physics of the various esophageal disorders and maps them onto a parameter space which we call the virtual disease landscape (VDL).
A multi-stage machine learning model on diagnosis of esophageal manometry
This diagnostic approach on motility disordered using HRM was mirrored using a multi-stage modeling framework developed using a combination of various machine learning approaches.
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