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Interpretable meta-learning of multi-omics data for survival analysis and pathway enrichment
MOTIVATION: Despite the success of recent machine learning algorithms’ applications to survival analysis, their black-box nature hinders interpretability, which is arguably the most important aspect. Similarly, multi-omics data integration for survival analysis is often constrained by the underlying...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079355/ https://www.ncbi.nlm.nih.gov/pubmed/36864611 http://dx.doi.org/10.1093/bioinformatics/btad113 |