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Enhanced Integrated Gradients: improving interpretability of deep learning models using splicing codes as a case study
Despite the success and fast adaptation of deep learning models in biomedical domains, their lack of interpretability remains an issue. Here, we introduce Enhanced Integrated Gradients (EIG), a method to identify significant features associated with a specific prediction task. Using RNA splicing pre...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305616/ https://www.ncbi.nlm.nih.gov/pubmed/32560708 http://dx.doi.org/10.1186/s13059-020-02055-7 |