Multi-centre benchmarking of deep learning models for COVID-19 detection in chest x-rays.

ABSTRACT:

Introduction

This study is a retrospective evaluation of the performance of deep learning models that were developed for the detection of COVID-19 from chest x-rays, undertaken with the goal of assessing the suitability of such systems as clinical decision support tools.

Methods

Models were trained on the National COVID-19 Chest Imaging Database (NCCID), a UK-wide multi-centre dataset from 26 different NHS hospitals and evaluated on independent multi-national clinical datasets. The evaluation considers clinical and technical contributors to model error and potential model bias. Model predictions are examined for spurious feature correlations using techniques for explainable prediction.

Results

Models performed adequately on NHS populations, with performance comparable

SUBMITTER: Harkness R 

PROVIDER: S-EPMC11148230 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature