Table 9.

Performance analysis of the proposed diagnosis methodology for COPD and pneumonia identification with current techniques on lung pathologies.

Classes	Method	Results (%)
Crackles, Crackles+ Wheeze, Normal, Wheeze [5]	STFT, WT, SVM	ACC: 49.86
Normal, Pneumonia [6]	SA	ACC: 91.98 SEN:92.06 SPE: 90.68
Pneumonia and Asthma [7]	NN	SEN: 89, SPE:100
Normal, Pneumonia [12]	WT, LR ANN	SEN: 94 SPE:63
Normal, Pneumonia [18]	EMD, KNN	ACC: 99.7
Normal, COPD and Pneumonia [20]	SA	-
Normal Asthma and COPD [22]	ANN	ACC:60.33 SEN: 65 SPE:54.2
Normal, Asthma, Bronchitis [24]	EMD, KNN	ACC: 99.3
COPD [25]	KT	ACC: 85.1
COPD [26]	KG, ML	ACC:95.1
COPD, Healthy, Pneumonia, Asthma, Bronchiectasis, Bronchiolitis [29]	CNN	SEN: 98.8 SPE:98.6
Crackles, Crackles+ Wheeze, Normal, Wheeze [28]	CNN	ACC i: 65.5 ii: 63.09
Normal, COPD, Pneumonia (This Method)	EMD, WT, QD	ACC: 99.8%

Knowledge graph: KG, Short-time Fourier Transform: STFT, Linear regression: LR, Statistical analysis: SA, Neural network: NN, Knowledge transfer: KT, ACC: Mean accuracy. SEN: Sensitivity, SPE: Specificity.