An uncertainty-aware self-training framework with consistency regularization for the multilabel classification of common computed tomography signs in lung nodules

BACKGROUND: Computed tomography (CT) signs of lung nodules play an important role in indicating lung nodules’ malignancy, and accurate automatic classification of these signs can help doctors improve their diagnostic efficiency. However, few relevant studies targeting multilabel classification (MLC)...

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Detalles Bibliográficos
Autores principales: Zhan, Ketian, Wang, Yunpeng, Zhuo, Yaoyao, Zhan, Yi, Yan, Qinqin, Shan, Fei, Zhou, Lingxiao, Chen, Xinrong, Liu, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10498222/
https://www.ncbi.nlm.nih.gov/pubmed/37711798
http://dx.doi.org/10.21037/qims-23-40

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10498222/
https://www.ncbi.nlm.nih.gov/pubmed/37711798
http://dx.doi.org/10.21037/qims-23-40

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