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Graph-based Fusion Modeling and Explanation for Disease Trajectory Prediction
We propose a relational graph to incorporate clinical similarity between patients while building personalized clinical event predictors with a focus on hospitalized COVID-19 patients. Our graph formation process fuses heterogeneous data, i.e., chest X-rays as node features and non-imaging EHR for ed...
| Autores principales: | , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Cold Spring Harbor Laboratory
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9628192/ https://www.ncbi.nlm.nih.gov/pubmed/36324799 http://dx.doi.org/10.1101/2022.10.25.22281469 |