High performance with fewer labels using semi-weakly supervised learning for pulmonary embolism diagnosis

Abstract This study proposes a semi-weakly supervised learning approach for pulmonary embolism (PE) detection on CT pulmonary angiography (CTPA) to alleviate the resource-intensive burden of exhaustive medical image annotation. Attention-based CNN-RNN models were trained on the RSNA pulmonary emboli...

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Библиографические подробности

Главные авторы:	Zixuan Hu, Hui Ming Lin, Shobhit Mathur, Robert Moreland, Christopher D. Witiw, Laura Jimenez-Juan, Matias F. Callejas, Djeven P. Deva, Ervin Sejdić, Errol Colak
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Nature Portfolio 2025-05-01
Серии:	npj Digital Medicine
Online-ссылка:	https://doi.org/10.1038/s41746-025-01594-2
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