Search Results for author: Peter J. Kahrilas

Found 3 papers, 0 papers with code

Neurological disorders leading to mechanical dysfunction of the esophagus: an emergent behavior of a neuromechanical dynamical system

no code implementations28 Feb 2024 Guy Elisha, Sourav Halder, Xinyi Liu, Dustin A. Carlson, Peter J. Kahrilas, John E. Pandolfino, Neelesh A. Patankar

Specifically, repetitive antegrade contractions (RACs) are conclusively shown to emerge from the coupled neuromechanical dynamics in response to sustained volumetric distension.

MRI-MECH: Mechanics-informed MRI to estimate esophageal health

no code implementations15 Sep 2022 Sourav Halder, Ethan M. Johnson, Jun Yamasaki, Peter J. Kahrilas, Michael Markl, John E. Pandolfino, Neelesh A. Patankar

Dynamic magnetic resonance imaging (MRI) is a popular medical imaging technique to generate image sequences of the flow of a contrast material inside tissues and organs.

Esophageal virtual disease landscape using mechanics-informed machine learning

no code implementations19 Nov 2021 Sourav Halder, Jun Yamasaki, Shashank Acharya, Wenjun Kou, Guy Elisha, Dustin A. Carlson, Peter J. Kahrilas, John E. Pandolfino, Neelesh A. Patankar

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).

BIG-bench Machine Learning

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