Clinical Variables, Deep Learning and Radiomics Features Help Predict the Prognosis of Adult Anti-N-methyl-D-aspartate Receptor Encephalitis Early: A Two-Center Study in Southwest China

OBJECTIVE: To develop a fusion model combining clinical variables, deep learning (DL), and radiomics features to predict the functional outcomes early in patients with adult anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis in Southwest China. METHODS: From January 2012, a two-center study of...

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Detalles Bibliográficos
Autores principales: Xiang, Yayun, Dong, Xiaoxuan, Zeng, Chun, Liu, Junhang, Liu, Hanjing, Hu, Xiaofei, Feng, Jinzhou, Du, Silin, Wang, Jingjie, Han, Yongliang, Luo, Qi, Chen, Shanxiong, Li, Yongmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Immunology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9199424/
https://www.ncbi.nlm.nih.gov/pubmed/35720336
http://dx.doi.org/10.3389/fimmu.2022.913703

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9199424/
https://www.ncbi.nlm.nih.gov/pubmed/35720336
http://dx.doi.org/10.3389/fimmu.2022.913703

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