PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging
Abstract Pulmonary embolism (PE) is a life-threatening clinical problem and computed tomography pulmonary angiography (CTPA) is the gold standard for diagnosis. Prompt diagnosis and immediate treatment are critical to avoid high morbidity and mortality rates, yet PE remains among the diagnoses most...
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| Auteurs principaux: | , , , , , , , , , , , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2020
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| Accès en ligne: | https://doaj.org/article/8ceb4d87e32c41efa595cc53fbb017ec |
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