# A Progressively Expanded Database for Automated Lung Sound Analysis: An Update
## 3 Results
### Performance Benchmark
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Segment Detection**} & \multicolumn{3}{c}{**Event Detection**} \\ \cline{2-10}  & **Accuracy** & **PPV** & **Sensitivity** & **Specificity** & **F1 Score** & **AUC** & **PPV** & **Sensitivity** & **F1 Score** \\ \hline \multicolumn{10}{l}{Inhalation} \\ \hline Train\_V1 & 0.915 \(\pm\) & 0.833 \(\pm\) & 0.781 \(\pm\) & 0.954 \(\pm\) & 0.806 \(\pm\) & 0.962 \(\pm\) & 0.818 \(\pm\) & 0.855 \(\pm\) & 0.836 \(\pm\) \\ on Test\_V1 & 0.001 & 0.006 & 0.010 & 0.003 & 0.004 & 0.001 & 0.005 & 0.009 & 0.005 \\ \hline Train\_V2 & 0.921 \(\pm\) & 0.849 \(\pm\) & 0.794 \(\pm\) & 0.959 \(\pm\) & 0.821 \(\pm\) & 0.968 \(\pm\) & 0.836 \(\pm\) & 0.864 \(\pm\) & 0.850 \(\pm\) \\ on Test\_V1 & 0.001 *** & 0.005 *** & 0.010 *** & 0.002 *** & 0.004 *** & 0.001 *** & 0.005 *** & 0.009 *** & 0.005 *** \\ \hline Train\_V1 & 0.927 \(\pm\) & 0.834 \(\pm\) & 0.789 \(\pm\) & 0.961 \(\pm\) & 0.811 \(\pm\) & 0.970 \(\pm\) & 0.819 \(\pm\) & 0.864 \(\pm\) & 0.842 \(\pm\) \\ on Test\_V2 & 0.002 & 0.009 & 0.010 & 0.003 & 0.005 & 0.001 & 0.007 & 0.009 & 0.005 \\ \hline Train\_V2 & 0.931 \(\pm\) & 0.844 \(\pm\) & 0.799 \(\pm\) & 0.963 \(\pm\) & 0.821 \(\pm\) & 0.973 \(\pm\) & 0.832 \(\pm\) & 0.869 \(\pm\) & 0.851 \(\pm\) \\ on Test\_V2 & 0.003 *** & 0.011 * & 0.012 * & 0.003 & 0.008 *** & 0.002 *** & 0.010 *** & 0.011 *** & 0.011 & 0.009 *** \\ \hline \multicolumn{10}{l}{Exhalation} \\ \hline Train\_V1 & 0.875 \(\pm\) & 0.750 \(\pm\) & 0.536 \(\pm\) & 0.957 \(\pm\) & 0.625 \(\pm\) & 0.901 \(\pm\) & 0.604 \(\pm\) & 0.629 \(\pm\) & 0.616 \(\pm\) \\ on Test\_V1 & 0.003 & 0.013 & 0.020 & 0.004 & 0.013 & 0.003 & 0.017 & 0.022 & 0.018 \\ \hline Train\_V2 & 0.882 \(\pm\) & 0.763 \(\pm\) & 0.573 \(\pm\) & 0.957 \(\pm\) & 0.654 \(\pm\) & 0.912 \(\pm\) & 0.626 \(\pm\) & 0.652 \(\pm\) & 0.639 \(\pm\) \\ on Test\_V1 & 0.004 *** & 0.011 ** & 0.026 *** & 0.003 & 0.018 *** & 0.005 *** & 0.026 * & 0.025 * & 0.025 * \\ \hline Train\_V1 & 0.923 \(\pm\) & 0.782 \(\pm\) & 0.630 \(\pm\) & 0.971 \(\pm\) & 0.698 \(\pm\) & 0.951 \(\pm\) & 0.751 \(\pm\) & 0.752 \(\pm\) & 0.752 \(\pm\) \\ on Test\_V2 & 0.002 & 0.009 & 0.018 & 0.002 & 0.011 & 0.002 & 0.011 & 0.020 & 0.015 \\ \hline Train\_V2 & 0.924 \(\pm\) & 0.783 \(\pm\) & 0.644 \(\pm\) & 0.970 \(\pm\) & 0.706 \(\pm\) & 0.954 \(\pm\) & 0.754 \(\pm\) & 0.749 \(\pm\) & 0.751 \(\pm\) \\ on Test\_V2 & 0.003 & 0.011 & 0.019 & 0.002 & 0.012 & 0.002 * & 0.017 & 0.019 & 0.017 \\ \hline \multicolumn{10}{l}{CAS} \\ \hline Train\_V1 & 0.852 \(\pm\) & 0.683 \(\pm\) & 0.448 \(\pm\) & 0.950 \(\pm\) & 0.540 \(\pm\) & 0.870 \(\pm\) & 0.470 \(\pm\) & 0.423 \(\pm\) & 0.446 \(\pm\) \\ on Test\_V1 & 0.004 & 0.014 & 0.031 & 0.005 & 0.022 & 0.008 & 0.025 & 0.029 & 0.026 \\ \hline Train\_V2 & 0.869 \(\pm\) & 0.702 \(\pm\) & 0.566 \(\pm\) & 0.942 \(\pm\) & 0.626 \(\pm\) & 0.911 \(\pm\) & 0.539 \(\pm\) & 0.489 \(\pm\) & 0.514 \(\pm\) \\ on Test\_V1 & 0.003 *** & 0.007 *** & 0.030 *** & 0.004 & 0.018 *** & 0.005 *** & 0.025 *** & 0.030 *** & 0.027 *** \\ \hline Train\_V1 & 0.873 \(\pm\) & 0.659 \(\pm\) & 0.383 \(\pm\) & 0.963 \(\pm\) & 0.484 \(\pm\) & 0.890 \(\pm\) & 0.379 \(\pm\) & 0.339 \(\pm\) & 0.359 \(\pm\) \\ on Test\_V2 & 0.002 & 0.010 & 0.032 & 0.004 & 0.024 & 0.006 & 0.028 & 0.030 & 0.028 \\ \hline Train\_V2 & 0.884 \(\pm\) & 0.675 \(\pm\) & 0.495 \(\pm\) & 0.956 \(\pm\) & 0.571 \(\pm\) & 0.918 \(\pm\) & 0.438 \(\pm\) & 0.403 \(\pm\) & 0.420 \(\pm\) \\ on Test\_V2 & 0.003 *** & 0.013 *** & 0.028 *** & 0.004 & 0.018 *** & 0.005 *** & 0.023 *** & 0.028 *** & 0.025 *** \\ \hline \multicolumn{10}{l}{DAS} \\ \hline Train\_V1 & 0.828 \(\pm\) & 0.733 \(\pm\) & 0.694 \(\pm\) & 0.888 \(\pm\) & 0.713 \(\pm\) & 0.894 \(\pm\) & 0.624 \(\pm\) & 0.593 \(\pm\) & 0.608 \(\pm\) \\ on Test\_V1 & 0.005 & 0.016 & 0.022 & 0.012 & 0.009 & 0.004 & 0.017 & 0.0