Development and validation of a deep learning-enhanced prediction model for the likelihood of pulmonary embolism
BackgroundPulmonary embolism (PE) is a common and potentially fatal condition. Timely and accurate risk assessment in patients with acute deep vein thrombosis (DVT) is crucial. This study aims to develop a deep learning-based, precise, and efficient PE risk prediction model (PE-Mind) to overcome the...
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Main Authors: | Yu Tian, Jingjie Liu, Shan Wu, Yucong Zheng, Rongye Han, Qianhui Bao, Lei Li, Tao Yang |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2025-02-01
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Series: | Frontiers in Medicine |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2025.1506363/full |
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