ReviewDiagnostics (Basel, Switzerland)2026
Artificial Intelligence for Detecting Aortic Arch Calcification on Chest Radiographs: A Systematic Review.
Krzysztof Żerdziński, Julita Janiec, Maja Dreger, Piotr Dudek, Iga Paszkiewicz, Adam Mitręga, Michał Bielówka, Alicja Nawrat, Jakub Kufel, Marcin Rojek
Abstract readReview
In one paragraphReview in Diagnostics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
10 authors.
Krzysztof ŻerdzińskiStudent Scientific Association of Computer Analysis and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Medical University of Silesia, 40-752 Katowice, Poland.ORCID 0009-0003-6581-8401 Julita JaniecStudent Scientific Association of Computer Analysis and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Medical University of Silesia, 40-752 Katowice, Poland.ORCID 0009-0002-0272-1226 Maja DregerStudent Scientific Association of Computer Analysis and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Medical University of Silesia, 40-752 Katowice, Poland.
Piotr DudekStudent Scientific Association of Computer Analysis and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Medical University of Silesia, 40-752 Katowice, Poland.ORCID 0000-0003-4767-7142 Iga PaszkiewiczDepartment of Anesthesiology and Intensive Therapy, Branch in Bielsko-Biała, Medical University of Silesia, 43-316 Bielsko-Biała, Poland.ORCID 0000-0002-0206-7044 Adam MitręgaStudent Scientific Association of Computer Analysis and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Medical University of Silesia, 40-752 Katowice, Poland.ORCID 0009-0004-3383-6477 Michał BielówkaStudent Scientific Association of Computer Analysis and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Medical University of Silesia, 40-752 Katowice, Poland.ORCID 0009-0007-0609-1678 Alicja NawratDepartment of Neonatal Intensive Care and Pathology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 41-800 Zabrze, Poland.ORCID 0000-0001-6615-1619 Jakub KufelDepartment of Radiology and Nuclear Medicine, Faculty of Medical Sciences in Katowice, Medical University of Silesia, 40-752 Katowice, Poland.ORCID 0000-0001-7633-3600 Marcin RojekStudent Scientific Association of Computer Analysis and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Medical University of Silesia, 40-752 Katowice, Poland.ORCID 0009-0005-0807-5423 Funding
No grant is acknowledged in the PubMed record.
6 · The paper itselfAbstract
PubMed holds no abstract for this paper.
Indexed as
aortic arch calcificationartificial intelligencecardiovascular riskchest radiographyconvolutional neural networksdeep learning
Identifiers
PMID41594218
PMCPMC12839748
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