Cargando…
All-Cause Death Prediction Method for CHD Based on Graph Convolutional Networks
Coronary heart disease (CHD) has become one of the most serious public health issues due to its high morbidity and mortality rates. Most of the existing coronary heart disease risk prediction models manually extract features based on shallow machine learning methods. It only focuses on the differenc...
Autores principales: | Xue, Yutao, Chen, Kaizhi, Lin, Huizhong, Zhong, Shangping |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9313992/ https://www.ncbi.nlm.nih.gov/pubmed/35898766 http://dx.doi.org/10.1155/2022/2389560 |
Ejemplares similares
-
Coronary heart disease prediction method fusing domain-adaptive transfer learning with graph convolutional networks (GCN)
por: Lin, Huizhong, et al.
Publicado: (2023) -
Acute coronary syndrome risk prediction based on gradient boosted tree feature selection and recursive feature elimination: A dataset-specific modeling study
por: Lin, Huizhong, et al.
Publicado: (2022) -
Graph Convolutional Network and Convolutional Neural Network Based Method for Predicting lncRNA-Disease Associations
por: Xuan, Ping, et al.
Publicado: (2019) -
GCNCPR-ACPs: a novel graph convolution network method for ACPs prediction
por: Wu, Xiujin, et al.
Publicado: (2022) -
Predicting anticancer hyperfoods with graph convolutional networks
por: Gonzalez, Guadalupe, et al.
Publicado: (2021)