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...

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Detalles Bibliográficos
Autores principales: Tariq, Amara, Tang, Siyi, Sakhi, Hifza, Celi, Leo Anthony, Newsome, Janice M., Rubin, Daniel L., Trivedi, Hari, Gichoy, Judy Wawira, Patel, Bhavik, Banerjee, Imon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2022
Materias:
Article
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

Internet

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

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