Perception and Awareness Towards Dental Artificial Intelligence

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Bol Artificial intelligence has revolutionized orthodontics. It has been employed for facial analysis, estimating the maturation level of cervical vertebrae, digitizing and tracing cephalometric landmarks with 90% accuracy, and predicting orthodontic outcomes. (Hanenkrath et al., 2025). Orthodontic research has investigated AI implementation in many fields, such as extraction decision-making, airway analysis, assessing the need for orthognathic surgery, and estimating facial aesthetics after orthognathic surgery to enhance accuracy and avoid bias from less-experienced professionals. (Topol, 2019; Khanagar et al., 2021a; Lin et al., 2023). This research constitutes the first original study conducted in Iraq to explore the perception and attitudes toward implementing dental artificial intelligence among orthodontic specialists. A validated survey was developed. Content validation was conducted through a rigorous two-round process using Lawshe's method with the involvement of six orthodontic experts. Face validity was evaluated using the percent agreement and Cohen's kappa statistics to assess inter-rater reliability, with two orthodontic experts involved in this evaluation.

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Artificial intelligence has revolutionized orthodontics. It has been employed for facial analysis, estimating the maturation level of cervical vertebrae, digitizing and tracing cephalometric landmarks with 90% accuracy, and predicting orthodontic outcomes. (Hanenkrath et al., 2025). Orthodontic research has investigated AI implementation in many fields, such as extraction decision-making, airway analysis, assessing the need for orthognathic surgery, and estimating facial aesthetics after orthognathic surgery to enhance accuracy and avoid bias from less-experienced professionals. (Topol, 2019; Khanagar et al., 2021a; Lin et al., 2023). This research constitutes the first original study conducted in Iraq to explore the perception and attitudes toward implementing dental artificial intelligence among orthodontic specialists. A validated survey was developed. Content validation was conducted through a rigorous two-round process using Lawshe's method with the involvement of six orthodontic experts. Face validity was evaluated using the percent agreement and Cohen's kappa statistics to assess inter-rater reliability, with two orthodontic experts involved in this evaluation.


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