A supervised machine learning-based methodology for analyzing dysregulation in splicing machinery: An application in cancer diagnosis.
Oscar Gabriel Reyes PupoEduardo PérezRaúl M. LuqueJusto CastañoSebastián VenturaPublished in: Artif. Intell. Medicine (2020)
Keyphrases
- supervised machine learning
- cancer diagnosis
- manually annotated
- lung cancer
- microarray
- cancer classification
- gene expression data
- colon cancer
- gene selection
- active learning
- supervised learning
- gene expression profiles
- feature selection
- machine learning methods
- reinforcement learning
- high quality
- information retrieval
- machine learning