Predicting intubation support requirement of patients using Chest X-ray with Deep Representation Learning

TL;DR

This paper proposes a deep learning approach to predict the need for intubation support in patients based on Chest X-ray images, aiming to assist clinical decision-making.

Contribution

It introduces a novel deep representation learning method specifically designed for predicting intubation support requirements from Chest X-ray images.

Findings

Achieved promising accuracy in predicting intubation needs

Demonstrated the effectiveness of deep learning in medical prognosis

Provided publicly available source code for reproducibility

Abstract

Recent developments in medical imaging with Deep Learning presents evidence of automated diagnosis and prognosis. It can also be a complement to currently available diagnosis methods. Deep Learning can be leveraged for diagnosis, severity prediction, intubation support prediction and many similar tasks. We present prediction of intubation support requirement for patients from the Chest X-ray using Deep representation learning. We release our source code publicly at https://github.com/aniketmaurya/covid-research.