Outcome prediction for salivary gland cancer using multivariate adaptative regression splines (MARS) and self-organizing maps (SOM).
Paloma Lequerica-FernándezIgnacio PeñaFrancisco Javier Iglesias-RodríguezCarlos González-GutiérrezJuan Carlos de VicentePublished in: Neural Comput. Appl. (2020)
Keyphrases
- self organizing maps
- outcome prediction
- regression model
- breast cancer
- genomic data
- logistic regression models
- neural network
- competitive learning
- model selection
- unsupervised learning
- neural gas
- gene expression datasets
- gene expression profiles
- prostate cancer
- topology preserving
- protein protein interaction networks
- som neural network
- input data
- k means
- multivariate data
- high throughput
- data management
- pattern recognition