Predicting intubation support requirement of patients using Chest X-ray with Deep Representation Learning
This work addresses the need for automated prognosis in medical imaging, specifically for COVID-19 patients, but is incremental as it applies deep representation learning to a known task.
The authors tackled the problem of predicting intubation support requirements for patients using chest X-rays, achieving a performance with an F1-score of 0.85 and an AUC of 0.92.
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.