开发和验证基于规则的算法,以使用结构化电子健康记录数据识别牙周病诊断
Bunmi Tokede1, Ryan Brandon2, Chun-Teh Lee3
1Department of Diagnostic and Biomedical Sciences, University of Texas at Houston, Health Science Center, Houston, Texas, USA.
Journal of clinical periodontology
|January 11, 2024
概括
使用电子健康记录 (EHR) 的自动化算法可以以中等准确性建议牙周诊断. 这种工具有助于临床医生,特别是那些经验较少的人,诊断牙周疾病和疾病.
科学领域:
- 牙周病学 牙周病学
- 牙科信息学 牙科信息学
- 医疗保健中的人工智能
背景情况:
- 准确的牙周诊断依赖于2017年世界研讨会分类.
- 电子健康记录 (EHR) 包含用于诊断的宝贵临床数据.
- 自动化诊断建议可以支持临床决策.
研究的目的:
- 开发和验证基于EHR的牙周诊断算法.
- 将诊断建议与2017年世界研讨会标准保持一致.
- 为了评估算法在牙周病的分期和分级的准确性.
主要方法:
- 使用EHR临床数据 (CAL,探测深度等) 代开发基于规则的算法. ) 的情况.
- 通过专家牙周科医生的手动图表审查进行验证.
- 基于专家反和数据限制,改进了算法.
主要成果:
- 最初的算法准确度:阶段为71.8%,阶段和等级为64.7%.
- 精细的算法准确度:阶段为79.6%,阶段和等级为68.8%.
- 在建议牙周病诊断方面表现出适度的准确性.
结论:
- 基于EHR的算法可以为牙周诊断提供中等准确度的支持.
- 该工具对经验较少的临床医生尤其有益.
- 算法的性能取决于EHR数据的质量和完整性.
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