First Deployment of a Portable, Bedside, Low-Field Magnetic Resonance Imaging Solution for Artificial Intelligence Based Application (2771)

Kevin N. Sheth; Bradley A. Cahn; Sadegh Salehi; Jill Shah; Samantha By; E. Brian Welch; Michael Sofka; Laura Sacolick; Matthew Ming Fai Yuen; Mercy H. Mazurek; Charles Matouk; Barbara Gordon‐Kundu; Adrienne Ward; Guido J. Falcone; Nils Petersen; Joseph Schindler; Emily Gilmore; David Y. Hwang; Kevin T. Gobeske; Jennifer Kim; Lauren Sansing; Gordon Sze; Matthew S. Rosen; W. Taylor Kimberly; Prantik Kundu

doi:10.1212/wnl.94.15_supplement.2771

Abstract

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To demonstrate proof-of-concept for a portable, bedside magnetic resonance imaging (MRI) in acute brain injury using artificial intelligence (AI) based determination of mass effect (ME).

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Sheth et al. (2020) studied this question.

synapsesocial.com/papers/6aad05eebc4f65364cd2197e https://doi.org/10.1212/wnl.94.15_supplement.2771

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Abstract

This is the authors' abstract. We don't add key points for this paper.

To demonstrate proof-of-concept for a portable, bedside magnetic resonance imaging (MRI) in acute brain injury using artificial intelligence (AI) based determination of mass effect (ME).

First Deployment of a Portable, Bedside, Low-Field Magnetic Resonance Imaging Solution for Artificial Intelligence Based Application (2771)

Abstract

Discussion

Cite This Study

First Deployment of a Portable, Bedside, Low-Field Magnetic Resonance Imaging Solution for Artificial Intelligence Based Application (2771)

Abstract

Discussion

Cite This Study

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