A promising approach for screening pulmonary hypertension based on frontal chest radiographs using deep learning: A retrospective study.

ABSTRACT:

Background

To date, the missed diagnosis rate of pulmonary hypertension (PH) was high, and there has been limited development of a rapid, simple, and effective way to screen the disease. The purpose of this study is to develop a deep learning approach to achieve rapid detection of possible abnormalities in chest radiographs suggesting PH for screening patients suspected of PH.

Methods

We retrospectively collected frontal chest radiographs and the pulmonary artery systolic pressure (PASP) value measured by Doppler transthoracic echocardiography from 762 patients (357 healthy controls and 405 with PH) from three institutes in China from January 2013 to May 2019. The wohle sample comprised 762 images (641 for training, 80 for internal test, and 41 for external test). We firstly

SUBMITTER: Zou XL 

PROVIDER: S-EPMC7380616 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature