Research Article
Early Diagnosis of Brain Tumour MRI Images Using Hybrid Techniques between Deep and Machine Learning
Table 6
Comparing the performance of the proposed systems with relevant studies.
| | Previous research | Accuracy (%) | Sensitivity (%) | Specificity (%) |
| | Sharif et al. [18] | 92.5 | — | — | | Dandu et al. [19] | 90.2 | — | — | | Amin et al. [20] | 87 | 92 | 80 | | Huang et al. [21] | 94.53 | — | — | | Kaur et al. [22] | 91.51 | 90.65 | 95.79 | | Kumar et al. [24] | 92.63 | 92.38 | 93.33 | | Afshar et al. [42] | 92.45 | 90.36 | 91.98 | | Bahadure et al. [43] | 92.03 | 92.36 | 91.42 | | Toğaçar et al. [44] | 87.93 | 84.38 | 92.31 | | Zollner et al. [45] | 85 | 89 | 84 | | Amarapur [46] | 89 | 85 | 91 | | Cho et al. [47] | 89.81 | 88.89 | 90.74 | | Ghassemi et al. [48] | 91.7 | 90.16 | 95.58 | | David et al. [49] | 85 | 87 | 79 | | Proposed model | 95.1 | 95.25 | 98.5 |
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