## 4 Discussion and Conclusions
Both for labelling and evaluation, if possible, more than one expert, coming from different specializations, should be enrolled in order to obtain multiple opinions. The final aim of this tool would be to prove that the CAD system effectively helps doctors in their diagnoses, it would be also important to evaluate the performance of the specialists with and without the help of the tool [10]. The main characteristics of our proposed baseline are stated in Table 3 and compared with each evaluated paper. Figure 2: Radar graphs for each paper. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Paper N\({}^{\circ}\)** & **AUC** & **Accuracy** & **Dataset Size** & **Sensitivity** & **Specificity** & **Labelling** \\ \hline Dimililer [9] & NA & 4.75 & 1.00 & NA & NA & NA \\ [PERSON] et al. [10] & 4.87 & N.A. & 4.00 & 4.71 & 4.75 & 5.00 \\ [PERSON] et al. [13] & 4.95 & 4.79 & 2.02 & 4.95 & 4.87 & 2.54 \\ [PERSON] et al. [15] & NA & 4.31 & 5.00 & NA & NA & NA \\ [PERSON] et al. [17] & 4.79 & NA & 1.72 & 4.59 & 4.51 & 1.00 \\ [PERSON] et al. [19] & NA & 4.83 & 1.01 & NA & NA & NA \\ [PERSON] et al. [21] & 4.91 & 4.63 & 3.00 & 4.91 & 4.35 & NA \\ [PERSON] et al. [24] & 4.91 & NA & 1.64 & 4.83 & 4.75 & 1.00 \\ [PERSON] et al. [26] & 4.71 & NA & 4.00 & 4.23 & 4.55 & NA \\ [PERSON] et al. [28] & 4.91 & 4.75 & 1.65 & NA & NA & 2.04 \\ [PERSON] et al. [30] & NA & 4.87 & 1.43 & 4.75 & 4.83 & NA \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Values extracted from Table 1 and mapped in the range from 1 to 5. In case of multiple and binary results we used just the binary one in order to relate different studies. For the dataset size, we considered [10,15,26] as outliers and mapped them to the values of 5 and 4. We then mapped the other values from 1 to 3. For the labelling, we computed the values using the formula \((N*0.5)+(Y*0.3)+(C*0.2)\) and a subsequent mapping from 1 to 5. Figure 3: Arbeitsgemeinschaft für Osteosynthesefragen (AO) partial classification for proximal femur fracture. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**Paper N\({}^{*}\)** & **Pre-Training Multiclass** & **Visualization (e.g., CAM)** & **Large Dataset (\(\geq\)2000)** & **Different Architectures** & **Data Augmentation** & **Cropping Phase** & **Cross Validation** & **\#Specialist** & **Assisted** \\ \hline Dimillier [9] & N & N & N & N & N & N & N & N & N \\ [PERSON] et al. [10] & Y & N & Y & Y & N & N & Y & N & Y & Y \\ [PERSON] et al. [11] & N & Y & N & N & N & Y & Y & Y & Y & N \\ [PERSON] et al. [15] & N & N & N & Y & Y & N & Y & N & - & N \\ [PERSON] et al. [17] & N & N & N & N & N & Y & Y & N & N & N \\ [PERSON] et al. [19] & N & N & N & N & N & Y & N & N & N & N \\ [PERSON] et al. [21] & Y & N & Y & Y & N & Y & N & N & - & N \\ [PERSON] et al. [24] & N & N & Y & N & Y & Y & N & N & N & N \\ [PERSON] et al. [26] & N & N & Y & Y & N & Y & N & N & Y & N \\ [PERSON] et al. [28] & N & Y & Y & N & Y & Y & Y & N & Y & N \\ [PERSON] et al. [30] & N & N & Y & N & Y & Y & Y & Y & - & N \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison between our proposed baseline and each paper. **Author Contributions:** Conceptualization, L.T. and E.V. ; methodology, L.T. and S.M. ; validation, L.T. ; formal analysis, L.T., R.M. and S.M. ; investigation, L.T. ; resources, L.T., R.M. and E.V. ; data curation, L.T. ; writing--original draft preparation, L.T. ; writing--review and editing, R.M., E.V. and S.M. ; supervision, R.M. and E.V. ; project administration, E.V. and S.M. ; funding acquisition, E.V., R.M. and S.M. All authors have read and agreed to the published version of the manuscript. **Funding:** This research received no external funding. **Conflicts of Interest:** The authors declare no conflict of interest.