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Interpretability of Input Representations for Gait Classification in Patients after Total Hip Arthroplasty
Many machine learning models show black box characteristics and, therefore, a lack of transparency, interpretability, and trustworthiness. This strongly limits their practical application in clinical contexts. For overcoming these limitations, Explainable Artificial Intelligence (XAI) has shown prom...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7471970/ https://www.ncbi.nlm.nih.gov/pubmed/32781583 http://dx.doi.org/10.3390/s20164385 |