Using machine learning of clinical data to diagnose COVID-19: a systematic review and meta-analysis.

ABSTRACT:

Background

The recent Coronavirus Disease 2019 (COVID-19) pandemic has placed severe stress on healthcare systems worldwide, which is amplified by the critical shortage of COVID-19 tests.

Methods

In this study, we propose to generate a more accurate diagnosis model of COVID-19 based on patient symptoms and routine test results by applying machine learning to reanalyzing COVID-19 data from 151 published studies. We aim to investigate correlations between clinical variables, cluster COVID-19 patients into subtypes, and generate a computational classification model for discriminating between COVID-19 patients and influenza patients based on clinical variables alone.

Results

We discovered several novel associations between clinical variables, including correlations betwee

SUBMITTER: Li WT 

PROVIDER: S-EPMC7522928 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature