Deep Convolutional Neural Networks Based Analysis of Cephalometric Radiographs for Differential Diagnosis of Orthognathic Surgery Indications
Abstract
:1. Introduction
2. Materials and Methods
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Parameter | Orthodontic Treatment | Orthognathic Surgery | Total |
---|---|---|---|
Number of patients | 159 | 174 | 333 |
Number of females/males | 88/71 | 93/81 | 181/152 |
Mean age (SD) | 22.7 (5.8) | 23.4 (4.9) | 23.1 (5.1) |
Model | AUC (95% CI) | Accuracy (95% CI) | Sensitivity (95% CI) | Specificity (95% CI) |
---|---|---|---|---|
Modified-Alexnet | 0.969 (±0.019) | 0.919 (±0.030) | 0.852 (±0.041) | 0.973 (±0.017) |
MobileNet | 0.908 (±0.032) | 0.838 (±0.429) | 0.761 (±0.051) | 0.931 (±0.028) |
Resnet50 | 0.923 (±0.030) | 0.838 (±0.429) | 0.750 (±0.052) | 0.944 (±0.025) |
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Lee, K.-S.; Ryu, J.-J.; Jang, H.S.; Lee, D.-Y.; Jung, S.-K. Deep Convolutional Neural Networks Based Analysis of Cephalometric Radiographs for Differential Diagnosis of Orthognathic Surgery Indications. Appl. Sci. 2020, 10, 2124. https://doi.org/10.3390/app10062124
Lee K-S, Ryu J-J, Jang HS, Lee D-Y, Jung S-K. Deep Convolutional Neural Networks Based Analysis of Cephalometric Radiographs for Differential Diagnosis of Orthognathic Surgery Indications. Applied Sciences. 2020; 10(6):2124. https://doi.org/10.3390/app10062124
Chicago/Turabian StyleLee, Ki-Sun, Jae-Jun Ryu, Hyon Seok Jang, Dong-Yul Lee, and Seok-Ki Jung. 2020. "Deep Convolutional Neural Networks Based Analysis of Cephalometric Radiographs for Differential Diagnosis of Orthognathic Surgery Indications" Applied Sciences 10, no. 6: 2124. https://doi.org/10.3390/app10062124