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Questions and Answers
What is the current accuracy level of AI applications in predicting early childhood caries?
What is the current accuracy level of AI applications in predicting early childhood caries?
- Above 80 percent
- Above 60 percent (correct)
- Between 50-60 percent
- Less than 50 percent
What is the primary limitation of using AI in pediatric dentistry?
What is the primary limitation of using AI in pediatric dentistry?
- Low performance in predicting non-response to silver diamine fluoride treatment
- High risk of bias in included studies
- Insufficient data to draw definitive conclusions (correct)
- Inability to detect early childhood caries
What is the outcome of silver diamine fluoride treatment that AI models can predict with high performance?
What is the outcome of silver diamine fluoride treatment that AI models can predict with high performance?
- Dental plaque detection
- Non-response to treatment (correct)
- Tooth identification and numbering
- Response to treatment
What is the risk of bias assessment outcome for the majority of domains in the included studies?
What is the risk of bias assessment outcome for the majority of domains in the included studies?
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What is an additional application of AI in pediatric dentistry beyond early childhood caries detection?
What is an additional application of AI in pediatric dentistry beyond early childhood caries detection?
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