Table 18.
Accuracy of machine learning papers.
| Studies | Datasets | X-Ray | MRI | CT Scan |
|---|---|---|---|---|
| S17 | Tested reports of Gaucher patients | No | 70% | No |
| S18 | 35 MRI images | No | 86% | No |
| S19 | Dataset of 18 images | No | 91% | No |
| S20 | (1) 36 BNC samples, (2) 40 control samples | No | 97% | No |
| S21 | Knee MRI reports | No | 95% | No |
| S22 | X-ray images of patients | 50% | No | No |
| S23 | (1) 21 images for training patella, (2) 48 images as the validation set | 80% | No | No |
| S24 | 432 images of the femur | 97.2% | No | No |
| S25 | 75,000 patients’ data | 95% | No | No |
| S26 | 24 X-ray images | 50% | No | No |
| S27 | 1024 X-ray images | 82.98% | No | No |
| S28 | Micro CT trabecular datasets | No | No | 65% |
| S29 | Multidetector Computed Tomography (MDCT) dataset | No | No | 98% |
| S30 | 10 knees-experienced patterns | No | No | 90% |
| S31 | Seven samples of pig femur bone | No | No | 65% |
| S32 | CT scan images of patients | No | No | 70% |
| Total Accuracy | 75.9% | 87.8% | 77.6% |