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Apollo
Article . 2025
License: CC BY
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Radiology Artificial Intelligence
Article . 2025 . Peer-reviewed
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A Pipeline for Automated Quality Control of Chest Radiographs

descriptionPublicationkeyboard_double_arrow_right Article 01 May 2025 English Publisher:Radiological Society of North America (RSNA)Journal:Radiology: Artificial Intelligence, volume 7 (eissn: 2638-6100, Copyright policy )Funded by:EC | NoMADS
Authors: Ian A. Selby; Eduardo González Solares; Anna Breger; Michael Roberts; Lorena Escudero Sánchez; Judith Babar; James H. F. Rudd; +39 Authors

doi: 10.1148/ryai.240003 , 10.17863/cam.116511

pmid: 40042404

A Pipeline for Automated Quality Control of Chest Radiographs

Abstract

This article presents a suite of quality control tools for chest radiographs based on traditional and artificial intelligence methods, developed and tested with data from 39 centers in seven countries.

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Keywords

Thoracic Radiography, Automated Quality Control, Artificial Intelligence, Data Standardization, Automated Data Curation

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
Green
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