Automated, Standardized, Quantitative Analysis of Cardiovascular Borders on Chest X-Rays Using Deep Learning

Deep learning-derived z-score analysis of CXR showed potential in classifying and stratifying the risk of cardiovascular abnormalities.

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Publication Details

Journal
JACC Advances
Published
2025-04-25
DOI
https://doi.org/10.1016/j.jacadv.2025.101687
Citations
2
Primary Topic
Cardiac Imaging and Diagnostics
Type
article
Field-Weighted Citation Impact
2.72
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article

Automated, Standardized, Quantitative Analysis of Cardiovascular Borders on Chest X-Rays Using Deep Learning

Seong Ho Park, Dong Hyun Yang, Cherry Kim, Gyu-Jun Jeong et al.
2 citations
JACC Advances
Cardiac Imaging and Diagnostics
2.72
article

Automated, Standardized, Quantitative Analysis of Cardiovascular Borders on Chest X-Rays Using Deep Learning

Seong Ho Park, Dong Hyun Yang, Cherry Kim, Gyu-Jun Jeong, Young‐Hak Kim, Eun Ju Chun, June‐Goo Lee, Iksung Cho, Jong Eun Lee, Duk‐Woo Park, Marly van Assen, Tae Joon Jun, Min Soo Cho, Hyun Jung Koo, Joon‐Won Kang, Joon Bum Kim, Young Joo Suh, Yura Ahn, Carlo N. De Cecco, Jung-Min Ahn, Sang Min Lee, Jung Bok Lee, Hongmin Oh, Joon Beom Seo, Hee‐Jun Kang, Sijoon Kim
article en
2 citations

Abstract

Deep learning-derived z-score analysis of CXR showed potential in classifying and stratifying the risk of cardiovascular abnormalities.

JACC AdvancesVol. 4(5)
Ulsan College (KR), Emory University (US), Yonsei University (KR), Korea University (KR), Severance Hospital (KR), Asan Medical Center (KR), Seoul National University Bundang Hospital (KR), Ansan University (KR), University of Ulsan (KR)
Good health and well-being
Openalex Percentile: Top 11%
Cardiac Imaging and Diagnostics
2.72
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