Interpretable CNN for ischemic stroke subtype classification with active model adaptation

BACKGROUND: TOAST subtype classification is important for diagnosis and research of ischemic stroke. Limited by experience of neurologist and time-consuming manual adjudication, it is a big challenge to finish TOAST classification effectively. We propose a novel active deep learning architecture to...

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Detalles Bibliográficos
Autores principales: Zhang, Shuo, Wang, Jing, Pei, Lulu, Liu, Kai, Gao, Yuan, Fang, Hui, Zhang, Rui, Zhao, Lu, Sun, Shilei, Wu, Jun, Song, Bo, Dai, Honghua, Li, Runzhi, Xu, Yuming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8729146/
https://www.ncbi.nlm.nih.gov/pubmed/34986813
http://dx.doi.org/10.1186/s12911-021-01721-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8729146/
https://www.ncbi.nlm.nih.gov/pubmed/34986813
http://dx.doi.org/10.1186/s12911-021-01721-5

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