Predicting intraventricular hemorrhage growth with a machine learning-based, radiomics-clinical model

We constructed a radiomics-clinical model to predict intraventricular hemorrhage (IVH) growth after spontaneous intracerebral hematoma. The model was developed using a training cohort (N=626) and validated with an independent testing cohort (N=270). Radiomics features and clinical predictors were se...

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Detalles Bibliográficos
Autores principales: Zhu, Dong-Qin, Chen, Qian, Xiang, Yi-Lan, Zhan, Chen-Yi, Zhang, Ming-Yue, Chen, Chao, Zhuge, Qi-Chuan, Chen, Wei-Jian, Yang, Xiao-Ming, Yang, Yun-Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2021
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8148477/
https://www.ncbi.nlm.nih.gov/pubmed/33946042
http://dx.doi.org/10.18632/aging.202954

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8148477/
https://www.ncbi.nlm.nih.gov/pubmed/33946042
http://dx.doi.org/10.18632/aging.202954

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