From:  Prognostic prediction of head and neck cancer through radiomics: a stacking ensemble approach with machine learning and deep learning models

 Performance of machine learning algorithms.

AlgorithmApplicationAccuracyReference
SVM (support vector machine): A supervised learning algorithm that finds the optimal hyperplane to separate data into classes with maximum margin.Oral SCC classification100%(Kumar et al., 2021) [13]
Random forest model with six decision trees and seven splits.Rectal cancer prognosis95.3%(Shen et al., 2020) [14]
Multiregional spatial interaction (MSI) matrix with 22 image features. A network strategy was used to integrate all image features and classify patients into different risk groups.Breast cancer prediction97.8%, to 98.6%(Wu et al., 2018) [15]
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