Table 5.
List of the diagnostic performance reported in the remaining studies
| Author (year) | Accuracy | Sensitivity | Specificity | Mean deviation from reference | AUC | Correlation against reference | ||||
|---|---|---|---|---|---|---|---|---|---|---|
| Alveolar bone resorption | ||||||||||
| Lin27 (2015) | NA | 92.5% /LOOCV; 92.8% /independent sample |
86.2% /LOOCV; 85.9% /independent sample |
NA | NA | NA | ||||
| Lin28 (2017) | NA | NA | NA | 9.5% | NA | NA | ||||
| Lee29 (2018) |
Identification of PCT
81.0% /premolar; 76.7% /molar Prediction of hopeless teeth 82.8% /premolar; 73.4% /molar |
NA | NA | NA |
Prediction of hopeless teeth
0.826/premolar; 0.734/molar |
NA | ||||
| Periapical lesions | ||||||||||
| Mol31 (1992) | 80.2% | 83.3% | 75.6% | NA | NA | 0.67 | ||||
| Carmody30 (2001) | 83.40% /automatic classification; 57.8% /manual classification |
NA | NA | NA | NA | 0.78/automatic classification; 0.44/manual classification |
||||
| Flores66 (2009) | 94.1% /reference: CBCT; 88.2% /reference: biopsy |
NA | NA | NA | NA | NA | ||||
| Maxillofacial cysts and tumors | ||||||||||
| Mikulka33 (2013) | 85% /follicular and radicular cysts; 81.8% /follicular cysts; 88.9% /radicular cysts |
NA | NA | NA | NA | NA | ||||
| Nurtanio34 (2013) | 87.18% | NA | NA | NA | 0.944 | NA | ||||
| Rana76 (2015) | NA | NA | NA | No significant difference | NA | NA | ||||
| Abdolali67 (2016) | NA | NA | NA | NA | 0.936 | 0.83/radicular cysts; 0.87/dentigerous cysts; 0.80/keratocysts |
||||
| Yilmaz69 (2017) | 100% /10-fold CV; 94% /LOOCV; 96% /split sample |
NA | NA | NA | NA | NA | ||||
| Abdolali68 (2017) | 94.29% /SVM; 96.48% /SDA |
NA | NA | NA | NA | NA | ||||
| Decision making model | ||||||||||
| Ngan74 (2016) | 93.02% | NA | NA | NA | NA | NA | ||||
| Son47 (2018) | 92.74% | NA | NA | NA | NA | NA | ||||
| Tooth types | ||||||||||
| Miki70 (2017) | 88.8% | NA | NA | NA | NA | NA | ||||
| Tuzoff46 (2019) | 99.87% /teeth numbering | 99.94% /teeth detection 98.00% /teeth numbering |
99.94% /teeth numbering | NA | NA | NA | ||||
| Identification of root canals | ||||||||||
| Benyó71 (2012) | 91.70% | NA | NA | NA | NA | NA | ||||
| Detection of maxillary sinusitis | ||||||||||
| Ohashi45 (2016) | Diagnostic performance of the AI model | |||||||||
| 73.50% | 77.60% | 69.40% | NA | NA | NA | |||||
| Change of diagnostic performance after the use of the AI model | ||||||||||
| Before | After | Before | After | Before | After | NA | Before | After | NA | |
| 66.0% /IEDs; 79.9% /experts |
73.4% /IEDs; 81.1% /experts |
63.4% /IEDs; 74.5% /experts |
71.6% /IEDs; 76.0% /experts |
68.6% /IEDs; 85.2% /experts |
75.30% /IEDs; 86.2% /experts |
0.728/IEDs; 0.871/experts |
0.780/IEDs; 0.897/experts |
|||
| Identification of inflamed gingiva | ||||||||||
| Rana73 (2017) | NA | NA | NA | NA | 0.746 | NA | ||||
| Identification of dental plaque | ||||||||||
| Yauney72 (2017) | 84.67% /RD; 87.18/CD |
NA | NA | NA | 0.769/RD; 0.872/CD |
NA | ||||
| Classification of the stages of the lower third molar development | ||||||||||
| De Tobel44 (2017) | 51% | NA | NA | 0.6 stages | NA | NA | ||||
| Detection of dental caries | ||||||||||
| Lee32 (2018) | 89.0% /premolar; 88.0% /molar; 82.0% /both |
84.0% /premolar; 92.3% /molar; 81.0% /both |
94.0% /premolar; 84.0% /molar; 83.0% /both |
NA | 0.917/premolar; 0.890/molar; 0.845/both |
NA | ||||
AUC, area under the receiver operating characteristic curve; CBCT, cone-beam CT; CD, commercial device; CV, cross-validation; IED, inexperienced dentist; LOOCV, leave-one-out cross-validation; NA, not available; NN, neural network; PCT, periodontally compromised teeth; RD, research device; SDA, sparse discriminant analysis; SVM, support vector machine.