人工智能用于牙裂唇和 palatal 患者的牙检测
Can Arslan1, Nesli Ozum Yucel1, Kaan Kahya1
1Department of Orthodontics, Faculty of Dentistry, Yeditepe University, Istanbul 34728, Turkey.
Diagnostics (Basel, Switzerland)
|January 8, 2025
概括
人工智能 (AI) 软件在发现和编号牙方面表现出高准确度,对于裂唇和 palatal 患者. 裂区域需要进一步精细化,特别是左侧,以改善临床应用.
科学领域:
- 牙科 牙科是指牙科的专业.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 裂口唇 (CLP) 呈现出独特的牙异常,使精确的牙识别复杂化.
- 对CLP患者有效的治疗计划依赖于精确的牙异常检测和编号.
- 人工智能 (AI) 具有提高牙科诊断精度的潜力,但其在CLP人群中的应用有限.
研究的目的:
- 评估AI软件在检测和编号CLP患者的牙方面的性能.
- 评估AI在这个群体中用于牙科识别的灵敏度,精度和特异性.
- 为了确定特定的解剖区域或人口群体,AI性能可能受到限制.
主要方法:
- 使用人工智能软件分析了100张6至15岁患者的全景射线图.
- 计算灵敏度,精度和特异性与四位正牙医的基本真相.
- 对跨年龄和性别的人工智能性能进行比较,重点关注具有挑战性的解剖区域.
主要成果:
- 人工智能系统实现了高整体灵敏度 (0.98 ± 0.03) 和精度 (0.96 ± 0.04).
- 没有观察到与年龄相关的显著性能差异 (p > 0.05).
- 在左上区域发现的挑战,具有较高的假阳性/假阴性率,与单边左裂患病率相关.
结论:
- 人工智能软件在CLP患者的牙科检测和编号方面是有效的.
- 进一步的AI改进是必要的,以提高裂区域的精度,特别是左侧.
- 解决AI的局限性可以增强其对复杂的面病例的临床实用性.
相关概念视频
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