Coronary heart disease prediction method fusing domain-adaptive transfer learning with graph convolutional networks (GCN)

Graph convolutional networks (GCNs) have achieved impressive results in many medical scenarios involving graph node classification tasks. However, there are difficulties in transfer learning for graph representation learning and graph network models. Most GNNs work only in a single domain and cannot...

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Detalles Bibliográficos
Autores principales: Lin, Huizhong, Chen, Kaizhi, Xue, Yutao, Zhong, Shangping, Chen, Lianglong, Ye, Mingfang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10471677/
https://www.ncbi.nlm.nih.gov/pubmed/37652917
http://dx.doi.org/10.1038/s41598-023-33124-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10471677/
https://www.ncbi.nlm.nih.gov/pubmed/37652917
http://dx.doi.org/10.1038/s41598-023-33124-z

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