Automated diagnosis and prognosis of COVID-19 pneumonia from initial ER chest X-rays using deep learning.

ABSTRACT:

Background

Airspace disease as seen on chest X-rays is an important point in triage for patients initially presenting to the emergency department with suspected COVID-19 infection. The purpose of this study is to evaluate a previously trained interpretable deep learning algorithm for the diagnosis and prognosis of COVID-19 pneumonia from chest X-rays obtained in the ED.

Methods

This retrospective study included 2456 (50% RT-PCR positive for COVID-19) adult patients who received both a chest X-ray and SARS-CoV-2 RT-PCR test from January 2020 to March of 2021 in the emergency department at a single U.S.

Institution

A total of 2000 patients were included as an additional training cohort and 456 patients in the randomized internal holdout testing cohort for a previously t

SUBMITTER: Chamberlin JH 

PROVIDER: S-EPMC9301895 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature