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预测主观认知衰退:使用动态贝叶斯网络的人工智能方法.

Antti Etholén1, Teemu Roos2, Mirja Hänninen1,3

  • 1Department of Public Health, University of Helsinki, Helsinki, Finland.

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PubMed
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这项研究使用人工智能来开发主观认知衰退 (SCD) 的风险评分,确定身体活动是关键的保护因素. 该工具有助于个性化预防策略,降低痴呆风险.

关键词:
在这里,我们可以看到AIAIAI.这就是为什么BMI是BMI.老化的老化 衰老的老化酒精消费 酒精消费 酒精消费人工智能的人工智能是人工智能.身体质量指数 (BMI) 是指身体质量指数.消费的水果和蔬菜的消费.痴呆症 痴呆症是一种痴呆症.失眠症状 失眠症状 失眠症状休时间 身体活动 活动吸烟是为了吸烟.

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科学领域:

  • 神经科学与公共卫生
  • 利用人工智能 (AI) 进行认知健康的预测建模.

背景情况:

  • 主观认知衰退 (SCD) 与可修改的风险因素有关.
  • 之前的SCD预测模型没有纳入发育风险因素模式.
  • 需要实用工具来防止认知能力下降.

研究的目的:

  • 使用人工智能方法检查风险因素的多因素轨迹及其与SCD的关联.
  • 开发一个得分计算器,用于预测以后的SCD.
  • 创建一个风险评分工具,用于个性化风险评估和干预计划,与痴呆症诊断相验证.

主要方法:

  • 采用动态贝叶斯网络,在赫尔辛基健康研究 (N=8960) 的五次重复调查 (2000-2022) 中接受培训.
  • 根据生活方式因素 (饮食,吸烟,酒精,体力活动,BMI,失眠) 预测的SCD (记忆,学习,集中),调整为共变量.
  • 使用5倍交叉验证和接收器操作特征 (ROC) 曲线分析评估模型性能.

主要成果:

  • 身体活动是SCD最强的预测因素 (OR 0.76).
  • 酒精消费与SCD之间呈现出U形关系.
  • 到2022年,SCD预测痴呆症诊断,记忆力下降将使痴呆症的可能性增加3-5倍 (AUC0.75-0.78).

结论:

  • 开发了一个人工智能驱动的风险评分工具,用于个性化SCD风险评估和干预.
  • 该工具可以帮助医疗保健专业人员指导生活方式干预措施,以减轻认知衰退和痴呆风险.
  • 通过人工智能模型早期识别SCD可以增强针对性痴呆症预防策略.