一个基于人工智能的模糊逻辑系统,用于对2型糖尿病患者的牙周炎风险评估
Ioana Scrobota1, Gilda Mihaela Iova1, Olivia Andreea Marcu2
1Department of Dental Medicine, Faculty of Medicine and Pharmacy, University of Oradea, 10 1st Decembrie Street, 410073 Oradea, Romania.
Bioengineering (Basel, Switzerland)
|March 28, 2025
概括
一个新的模糊系统使用生物标志物估计糖尿病患者的牙周炎风险. 这种方法与牙周口袋深度有显著的相关性,有助于早期诊断和跨学科护理.
科学领域:
- 生物医学工程 生物医学工程
- 数据科学数据科学数据科学
- 牙周病学 牙周病学
背景情况:
- 在全球范围内,牙周炎的患病率正在上升.
- 牙周炎和糖尿病之间存在双向关系.
- 需要新的DM生物标志物的查方法来治疗牙周炎.
研究的目的:
- 开发一种模糊系统来估计DM患者牙周炎风险.
- 利用现有的患者数据进行风险评估.
- 改善糖尿病患者牙周炎的早期检测和治疗.
主要方法:
- 从87名DM患者收集了身体质量指数 (BMI),血糖 (G),总胆固醇 (C) 和甘油三 (T) 的数据.
- 开发了一个有两个阶段的模糊系统:PRisk1 (BMI,G) 和PRisk2 (C,T),导致累积牙周炎风险 (PCRisk).
- 使用25个成员函数将语言术语和等级分配给数值变量;统计处理PCRisk和牙周口袋数量 (nrPP).
主要成果:
- 模糊系统成功估计了使用BMI,G,C和T的牙周炎风险.
- 在累积牙周炎风险 (PCRisk) 和牙周口袋数量 (nrPP) 之间发现了显著的相关性.
- 对于PCRisk每增加1.881个单位,nrPP增加1个单位.
结论:
- 基于模糊逻辑的系统有效估计了2型糖尿病患者的牙周炎风险.
- 该系统显示了与牙周口袋深度的显著相关性,表明了早期诊断的潜力.
- 研究结果支持改善DM和牙周炎患者的跨学科护理.
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