Research Article
[Retracted] Deep Learning Model for Automatic Classification and Prediction of Brain Tumor
Table 7
Comparison with existing state-of-art models.
| Study | Dataset source | No. of images | Technique used | Accuracy |
| Gu et al. [1] | REMBRANDT | 3064 | CDLLC on CNN | 96.39% | Deepak et al. [2] | Figshare | 1426 | SVM with CNN | 95.82% | Kumar et al. [3] | Figshare | 3064 | RNGAP model on CNN | 97.08% | Rehman et al. [4] | BraTS 2018 | 1074 | 3DCNN | 92.67% | Rajasree et al. [5] | BraTS 2015 | 374 | MSMCNN | 96.36% | Abd El Kader et al. [6] | Figshare | 3064 | HSANN | 97.33% | Bodapati et al. [7] | BraTS 2018 | 1074 | ELM | 97.8% | Mzoughi et al. [8] | BraTS 2018 | 1074 | 3DCNN | 96.49% | Sajjad et al. [9] | Radiopaedia | 121 | Deep-CNN | 94.58% | Abiwinanda. et al. [10] | Figshare | 3064 | CNN | 84.19% | Proposed methodology | Kaggle | 1800 | VGG19 | 98% |
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