Research Article
A Novel Method for Differential Prognosis of Brain Degenerative Diseases Using Radiomics-Based Textural Analysis and Ensemble Learning Classifiers
Table 2
Comparison with similar studies.
| Research study | Year | Dataset | Brain area | Classifier | Accuracy |
| Ahmad Chaddad [32] | 2018 | OASIS-1 | Hippocampus Amygdala | Random forest Random forest | 84.09% | CNN | 92.5% | Feng Feng [33] | 2018 | Local hospital data | Hippocampus | SVM | 86.75% | Yupeng Li and Jiehui Jiang [34] | 2019 | Local hospital data | Hippocampus | SVM | 91.5% | Kun Zhao [35] | Jan 2020 | ADNI | Hippocampus | SVM | 88.21% | Tao-Ran Li [36] | Dec 2020 | ADNI | Right posterior and left superior cingulate Gyrus | SVM | 95.9% | Current study proposed by us | 2021 | OASIS-3 | Whole brain | Ensemble classifiers | | XGBoost | 97.38% | AdaBoost | 97.21% | Bagging | 87.56% | Random forest | 87.72% |
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