## 3 Results
### \"Unambiguous\" Data Sample  
The patients' characteristics from the \"unambiguous\" data sample (1084 PETs) are provided in Table 1.  
A total of 909 patients (92%) had one PET and 77 patients (8%) had two or more PETs. The training procedure took 20 h 30 min (with a mean of 4 h 06 min per block) and the loss curves showed that the CNN learned efficiently (Figure 3).  
The learning process was stopped after 18 epochs. The results of the 5-fold cross validation are provided in Table 2.  
\begin{table}
\begin{tabular}{l l c c} \hline  & **Overall** & **Training Set** & **Test Set** \\ \hline n & 1084 & 976 & 108 \\ \hline Age in years & 58.5 \(\pm\) 14.7 & 58.5 \(\pm\) 14.9 & 58.5 \(\pm\) 13.5 \\ \hline Weight in kg & 72.1 \(\pm\) 16 & 72.2 \(\pm\) 16 & 71.3 \(\pm\) 16.3 \\ \hline Activity in MBq & 251.7 \(\pm\) 57 & 252 \(\pm\) 57 & 248.9 \(\pm\) 57.8 \\ \hline \multirow{2}{*}{Sex} & F & 481 (44.4\%) & 440 (45.1\%) & 41 (38\%) \\ \cline{2-4}  & M & 603 (55.6\%) & 536 (54.9\%) & 67 (62\%) \\ \hline \multirow{2}{*}{Clinical context} & Oncological & 940 (86.7\%) & 847 (86.8\%) & 93 (86.1\%) \\ \cline{2-4}  & Non-Onecological & 144 (13.3\%) & 129 (13.4\%) & 15 (13.9\%) \\ \hline \multirow{2}{*}{Label} & Normal & 520 (48\%) & 468 (48\%) & 52 (48.1\%) \\ \cline{2-4}  & Abnormal & 564 (52\%) & 508 (52\%) & 56 (51.9\%) \\ \hline \end{tabular}
\end{table}
Table 1: Patients’ characteristics from the “unambiguous” data sample.  
Figure 3: Evolution of the loss function on the training set (**a**) and the validation set (**b**) as a function of the number of steps during the cross validation. Each colored curve represents the loss function of a fold.  
\begin{table}
\begin{tabular}{l c c c c c c c c c c c c} \hline  & **TP** & **TN** & **FP** & **FN** & **NPV (\%)** & **PPV (\%)** & **Sensitivity (\%)** & **Specificity (\%)** & **Accuracy (\%)** & **F1 Score (\%)** & **LR+** & **LR–** \\ \hline fold 1 & 96 & 94 & 0 & 6 & 94.0 & 100 & 94.1 & 100 & 96.9 & 97.0 & \(>\)100 & 0.059 \\ \hline fold 2 & 85 & 92 & 1 & 17 & 84.4 & 98.8 & 83.3 & 96.9 & 90.8 & 90.4 & 75.727 & 0.169 \\ \hline fold 3 & 91 & 92 & 1 & 11 & 89.3 & 98.9 & 89.2 & 98.9 & 93.8 & 93.8 & 81.091 & 0.109 \\ \hline fold 4 & 89 & 94 & 0 & 12 & 88.7 & 100 & 88.1 & 100 & 93.8 & 93.7 & \(>\)100 & 0.119 \\ \hline fold 5 & 89 & 92 & 2 & 12 & 88.5 & 97.8 & 88.1 & 97.9 & 92.8 & 92.7 & 41.952 & 0.122 \\ \hline Mean & 90 & 92.8 & 0.8 & 11 & 89.0 & 99.1 & 88.6 & 99.1 & 93.6 & 93.5 & 66.257 & 0.116 \\ \hline Variance & 16 & 1.2 & 0.7 & 15 & 0.1 & 0 & 0.1 & 0 & 0 & 0.1 & 450.223 & 0.002 \\ \hline Std deviation & 4,00 & 1,09 & 0.84 & 3,91 & 3.4 & 0.9 & 3.8 & 0.9 & 2.2 & 2.4 & 21,218 & 0.039 \\ \hline \end{tabular}
\end{table}
Table 2: Results of the 5-fold cross validation of the “unambiguous” data sample.  
Fold 1 provided the best results, with a Sen of 94%, Spe of 100%, PPV and NPV of 100% and 94%, respectively, corresponding to an F1 score of 97%. The pretrained CNN then analyzed the independent remaining test set (108 PETs) and achieved a Se of 84% and Spe of 98%, a PPV and NPV of 98% and 85%, respectively, a F1 score of 90% and LR+ and LR- of 42 and 16%, respectively. The heatmaps derived from the gradient weighted-class activation map method (Grad-CAM) [16] for one patient are provided in Figure 4.  
The pretrained CNN then analyzed the remaining database composed of the \"ambiguous\" PETs (3911 PETs) and achieved a Se of 26% and Spe of 86%, a PPV and NPV of 97.8% and 5%, respectively, and a F1 score of 0.41.