Review Article
Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries
Table 1
Risk of bias. Red cross indicates no and green tick indicates yes.
| Criteria | Author, year | Devito et al., 2008 | Mayank et al., 2017 | Casalegno et al., 2018 | Leea et al., 2018 | Zanella et al., 2018 | Moutselos et al., 2019 | Patil et al., 2019 | Javed et al., 2019 | Hung et al., 2019 | Geetha et al., 2020 | Duong et al., 2021 | Kühnisch et al., 2022 |
| Inclusion criteria | ✓ | ✓ | ✓ | ✓ | | ✓ | | | ✓ | ✓ | ✓ | ✓ | Exclusion criteria | ✓ | ✓ | ✓ | ✓ | ✓ | | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | Feature extraction criteria | | ✓ | ✓ | | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | | ✓ | Description of diagnosis dental caries | ✓ | ✓ | ✓ | | ✓ | ✓ | | | | ✓ | ✓ | ✓ | Radiographs examination for dental caries diagnosis | ✓ | | | ✓ | | | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | Machine learning algorithm description | ✓ | | | ✓ | ✓ | ✓ | ✓ | ✓ | | ✓ | ✓ | | Samples of dataset >149 | ✓ | ✓ | ✓ | ✓ | ✓ | | | ✓ | ✓ | | ✓ | ✓ | Description of testing and training evaluation | | | | | ✓ | | | | | | | | Statistical and evaluation | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | Risk of bias | Low | Low | Low | Low | Low | Moderate | Moderate | Moderate | Low | Low | Low | Low |
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