最后一次去看牙医和牙损失的严重程度:一种机器学习方法
1School of Dentistry, Federal University of Mato Grosso do Sul, Campo Grande, Brazil. aiello.rafael@gmail.com.
BMC research notes
|November 24, 2023
概括
延迟去看牙医与成人和老年人的牙损失有关. 机器学习有效地识别出牙脱落风险较高的人,帮助预防性护理策略.
科学领域:
- 口腔健康研究 口腔健康研究
- 公共卫生 公共卫生
- 生物统计学 生物统计学
背景情况:
- 社会经济地位显著影响口腔健康结果,包括牙损失.
- 定期去看牙医对于保持牙功能和预防严重的牙损失至关重要.
- 预测建模可以确定有针对性的干预措施的风险人群.
研究的目的:
- 检查最后一次去看牙医在社会经济地位和牙脱落之间的关系中的作用.
- 开发和验证一种机器学习模型,用于预测成人和老年人的牙损失风险.
主要方法:
- 分析了一大批代表性样本,包括88531名18岁及以上的巴西人.
- 使用结构方程模型 (SEM) 来评估牙医诊断频率与牙损失结果之间的关联.
- 使用机器学习算法进行预测模型培训和测试.
主要成果:
- 对于成年人来说,牙科访问间隔超过两年与缺乏功能牙相关.
- 在老年人群中,不经常去看牙医与严重的牙损失有关.
- 机器学习模型在预测牙损失风险方面表现高 (AUC 90%,准确度 90%),年龄是关键预测因素.
结论:
- 不经常去看牙医 (超过两年) 与缺乏功能性牙和严重的牙损失有关.
- 机器学习模型显示,在准确识别牙损失高风险的个体方面,有很大的潜力.
- 调查结果强调了及时牙科护理的重要性,并强调了预测分析在公共口腔健康中的实用性.
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