Table 2 Performance of artificial intelligence algorithms in identifying implants for total knee arthroplasty

Belete et al., 2021 [22]

Hyperparameter, Manual Segmentation Pre-Processing, Data Augmentation

ResNet-18

1

100%

NR

NR

NR

Bonnin et al., 2023 [23]

Exam Quality Control CNN Deep Learning

X-TKA

NR

99.9%

99.8%

100%

100%

Ghose et al. 2020 [26]

Histogram Equalization Data Augmentation, Albumentations Deep Learning DCNN

MobileNetV2

NR

96.7%

NR

NR

NR

Karnuta et al., 2021 [7, 8]

DCNN

InceptionV3

0.992

98.9%

94.6%

94.6%

99.4%

Klemt et al., 2022 [30]

CNN Preprocessing Hyp,erparameter Optimization, Class Activation Heat Maps

InceptionV3

NR

Primary TKA: 97.4%

Revision TKA: 96.3%

Primary TKA: 94.9%

Revision TKA: 94.5%

NR

Primary TKA: 97.8%

Revision TKA: 98.1%

Patel et al., 2021 [31]

DCNN, Hyperparameter Optimization, Image Segmentation/Data Augmentation Ensembled Networks

EfficientNet & U-Net

NR

98.9%

Human: 76.1%

98.9%

99%

NR

Sharma et al., 2021 [34]

BRISQUE Data Augmentation Fine-Tuning in Transfer Learning DCNN

ResNet-50v2, VGG16, MobileNetV2, DenseNet-201

0.9857

96.4%

97.20%

NR

NR

Tiwari et al., 2022 [20]

Transfer Machine Learning Models

ResNet-50, MobileNet, Efficient Net B7, InceptionV3, Nasnet, VGG16, Xception, Human

NR

ResNet-50-51.4%

MobileNet -99.6%

Efficient Net B7 -22.2%

InceptionV3-96.2%

Nasnet-94.6%

VGG16-99.0%

Xception-93.1%

Human-78.2%

ResNet-50-42.0%

MobileNet-99.6%

Efficient Net B7-22.2%

InceptionV3-96.2%

Nasnet-94.6%

VGG16-99.0%

Xception-93.1%

Human-50.0%

ResNet-50-62.0%

MobileNet-99.6%

Efficient Net B7-22.2%

InceptionV3-96.2%

Nasnet-94.6%

VGG16-99.0%

Xception-93.4%

Human-80.1%

NR

Yi et al., 2020 [35]

Data Augmentation DCNN

ResNet-18

1

100%

100%

100%

100%

Median (IQR)

NA

NA

0.996 (0.990–1)

98.9% (96.9%–99.8%)

98.1% (94.8%–99.7%)

99.6% (99.0%–100%)

99.4% (98.1%–100%)