## 7 Conclusions
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Author** & **Biomarker** & **Dataset** & **Classifer** & **AD/HC** & \begin{tabular}{c} **Validation** \\ **Method** \\ \end{tabular} & **ACC (\%)** & **SEN (\%)** & **SPE (\%)** \\ \hline [PERSON] et al. [46] & MRI & ADNI & SVM & 51/52 & Ten-fold & 86.2 & 86 & 86.3 \\ \hline [PERSON] et al. [47] & MRI & ADNI & \begin{tabular}{c} OPLS \\ MVA \\ \end{tabular} & 96/111 & Ten-fold & 87 & 83.3 & 90.193 \\ \hline [PERSON] et al. [48] & MRI & ADNI & \begin{tabular}{c} SVM, \\ OPLS \\ \end{tabular} & 116/110 & Ten-fold & 84.9 & 80.2 & 90.88 \\ \hline [PERSON] et al. [50] & MRI & ADNI & SVM & 59/127 & Two-fold & 78.2 & 68.5 & 81.7 \\ \hline [PERSON] al. [51] & MRI & OASIS & KNN & 49/49 & Ten-fold & 85 & 78 & 92 \\ \hline [PERSON] et al. [52] & MRI & ADNI & SVM & 188/229 & Ten-fold & 88.49 & 85.11 & 91.27 \\ \hline [PERSON] et al. [7] & MRI & ADNI & SVM & 130/130 & Ten-fold & 89.65 & 87.73 & 91.57 \\ \hline [PERSON] et al. [8] & MRI & ADNI & SVM & 130/130 & Ten-fold & 92.48 & 91.07 & 93.89 \\ \hline [PERSON] et al. [53] & MRI & ADNI & SVM-RFE & 54/58 & Five-fold & 92.86 & 87.04 & 98.28 \\ \hline [PERSON] et al. [4] & MRI & OASIS & NN & 49/49 & Ten-fold & 86 & 80 & 92 \\ \hline [PERSON] et al. [9] & MRI & OASIS & FNN & 28/98 & Five-fold & 90.06 \(\pm\) 0.01 & 92.00 \(\pm\) 0.04 & 87.78 \(\pm\) 0.04 \\ \hline [PERSON] et al. [10] & MRI & OASIS & MLP & 28/98 & Five-fold & 92.40 \(\pm\) 0.83 & 92.14 \(\pm\) 4.39 & 92.47 \(\pm\) 1.23 \\ \hline \multirow{4}{*}{Proposed Method} & MRI & \begin{tabular}{c} ADNI \\ (ROI\_CL) \\ \end{tabular} & BR-NN & 74/74 & \begin{tabular}{c} Average of ten \\ iterations * \\ \end{tabular} & 97.78 \(\pm\) 1.7 & 100.00 \(\pm\) 0.00 & 95.83 \(\pm\) 2.22 \\ \cline{1-1}  & MRI & \begin{tabular}{c} GARD \\ (ROI\_CL) \\ \end{tabular} & BR-NN & 42/42 & \begin{tabular}{c} Average of ten \\ iterations * \\ \end{tabular} & 80.95 \(\pm\) 4.45 & 61.9 \(\pm\) 8.91 & 100.00 \(\pm\) 0.00 \\ \cline{1-1}  & MRI & \begin{tabular}{c} ADNI \\ (ROI\_AAL) \\ \end{tabular} & BR-NN & 74/74 & \begin{tabular}{c} Average of ten \\ iterations * \\ \end{tabular} & 98.22 \(\pm\) 0.99 & 100 & 96 \(\pm\) 2.24 \\ \cline{1-1}  & MRI & \
\begin{tabular}{c} GARD \\ (ROI\_CAL) \\ \end{tabular} & BR-NN & 42/42 &
\begin{tabular}{c} Average of ten \\ iterations * \\ \end{tabular} & 90.48 \(\pm\) 2.45 & 71.43 \(\pm\) 6.30 & 100 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of the proposed method with other methods. * Number of hidden layers = 17, trained on 70% of ADNI dataset, Test set: 30% ADNI, 100% GARD. Abbreviations: Orthogonal Partial Least Squares (OPLS), Multivariate analysis (MVA), SVM Recursive Feature Elimination (SVM-RFE), Feedforward Neural Network (FNN), Multilayer Perceptron (MLP). the AD/ADD detection using T1-MRI yields significant improvement over the previously used VBM based method, at the same time, our findings of brain ROIs can help clinicians to focus on those specific regions for further future discovery. Hence, we hope our attempt will have some meaningful contribution in the future. The following are available online at [[https://www.mdpi.com/article/10.3390/app11136175/s1](https://www.mdpi.com/article/10.3390/app11136175/s1)]([https://www.mdpi.com/article/10.3390/app11136175/s1](https://www.mdpi.com/article/10.3390/app11136175/s1)). Includes four files showing the results of ROI analysis for the ADNI and GARD datasets. A separate excel file is included for a detailed demographics study with subject ID, CDR, MMSE score, age, imaging protocol, and other information of ADNI participants. Also,,m file and extracted features (xlsx) for code implementation. [PERSON] and [PERSON] contributed equally to this work. [PERSON] worked in conceptualization, simulation, validation, and manuscript writing of this paper. [PERSON] worked conceptualization and validation. [PERSON], [PERSON], and [PERSON] worked in resources, data curation, and investigation.