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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2021
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Materias: | |
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 |
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