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A novel kernel based approach to arbitrary length symbolic data with application to type 2 diabetes risk
Predictive modeling of clinical data is fraught with challenges arising from the manner in which events are recorded. Patients typically fall ill at irregular intervals and experience dissimilar intervention trajectories. This results in irregularly sampled and uneven length data which poses a probl...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8943170/ https://www.ncbi.nlm.nih.gov/pubmed/35322076 http://dx.doi.org/10.1038/s41598-022-08757-1 |