Development and validation of a lung graph–based machine learning model to predict acute pulmonary thromboembolism on chest noncontrast computed tomography

BackgroundComputed tomography pulmonary angiography (CTPA) is a first-line noninvasive method to diagnose acute pulmonary thromboembolism (APE); however, whether chest noncontrast CT (NC-CT) could aid in the diagnosis of APE remains unknown. The aim of this study was to build and evaluate a holistic...

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Veröffentlicht in:Quantitative imaging in medicine and surgery 2023-10, Vol.13 (10), p.6710-6723
Hauptverfasser: Deng, Mei, Liu, Anqi, Kang, Han, Xi, Linfeng, Yu, Pengxin, Xu, Wenqing, Yang, Haoyu, Xie, Wanmu, Liu, Min, Zhang, Rongguo
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Sprache:eng
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