Table 5.

Performance comparison of different approaches

Method	Accuracy	Remarks
SVM and deep learning	95.4%	Automatic feature generation by ResNet; Input: X-ray image
Vote based deep learning	98.2%	Image data
CNN with transfer learning	97.8%	Input: X-ray images
ML approach (WEKA)	91.4%	Input: Clinical data
Proposed method (SVM and IABC)	96.0%	Input: Clinical symptoms data
Gradient boosting	AuPR: 0.66	Input: Clinical symptoms data