An automated COVID-19 triage pipeline using artificial intelligence based on chest radiographs and clinical data – DocWire News

This article was originally published here

NPJ Digit Med. 2022 Jan 14;5(1):5. doi: 10.1038/s41746-021-00546-w.

ABSTRACT

While COVID-19 diagnosis and prognosis artificial intelligence models exist, very few can be implemented for practical use given their high risk of bias. We aimed to develop a diagnosis model that addresses notable shortcomings of prior studies, integ…….

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This article was originally published here

NPJ Digit Med. 2022 Jan 14;5(1):5. doi: 10.1038/s41746-021-00546-w.

ABSTRACT

While COVID-19 diagnosis and prognosis artificial intelligence models exist, very few can be implemented for practical use given their high risk of bias. We aimed to develop a diagnosis model that addresses notable shortcomings of prior studies, integrating it into a fully automated triage pipeline that examines chest radiographs for the presence, severity, and progression of COVID-19 pneumonia. Scans were collected using the DICOM Image Analysis and Archive, a system that communicates with a hospital’s image repository. The authors collected over 6,500 non-public chest X-rays comprising diverse COVID-19 severities, along with radiology reports and RT-PCR data. The authors provisioned one internally held-out and two external test sets to assess model generalizability and compare performance to traditional radiologist interpretation. The pipeline was evaluated on a prospective cohort of 80 radiographs, reporting a 95% diagnostic accuracy. The study mitigates bias in AI model development and demonstrates the value of an end-to-end COVID-19 triage platform.

PMID:35031687 | DOI:10.1038/s41746-021-00546-w

Source: https://www.docwirenews.com/abstracts/an-automated-covid-19-triage-pipeline-using-artificial-intelligence-based-on-chest-radiographs-and-clinical-data-5/