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使用机器学习方法预测医疗保险受益人的认知障碍

Zongliang Yue¹, Sara Jaradat¹, Jingjing Qian¹

¹Auburn University Harrison College of Pharmacy, Auburn, AL, USA.

Archives of gerontology and geriatrics

|September 11, 2024

概括

机器学习模型预测了老年人的认知障碍. 基线认知功能和日常生活活动是关键预测因素,强调需要定期查.

科学领域:

老年学是一门学科.
医疗信息学医疗信息学
公共卫生公共卫生

背景情况:

认知障碍在老年人群中越来越令人担忧.
早期预测和干预对于管理认知衰退至关重要.

研究的目的:

开发和评估用于预测医疗保险受益人的认知障碍的机器学习模型.
确定老年人认知能力下降的关键预测因素.

主要方法:

对医疗保险当前受益者调查数据 (2016-2019年) 的回顾性分析.
使用人口,功能,健康和社会经济因素开发的机器学习算法.
模型使用准确度,AUC和F1得分进行评估;特征重要性通过基尼减值进行评估.

主要成果:

11.1%的65岁以上受益者表现出中度至严重的认知障碍.
基线认知功能,日常生活工具活动 (IADL),社交活动和日常生活活动 (ADL) 是显著的预测因素.
对于80岁以上的受益者来说,对医疗保健质量的满意度是最重要的预测因素.

结论:

基线认知功能和IADL是预测认知障碍的主要指标.
建议老年人定期进行认知和日常功能状态的查和监测.

关键词:

认知功能认知功能认知障碍认知障碍是一种认知障碍.机器学习是机器学习.美国医疗保险 (Medicare) 的医疗保险.年龄较大的成年人.

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