开发基于人工神经网络的成功衰老的智能预测系统
Raoof Nopour1, Hadi Kazemi-Arpanahi2
1Department of Health Information Management, Iran University of Medical Sciences, Tehran, Iran.
International journal of preventive medicine
|April 2, 2024
概括
这项研究开发了一种使用人工神经网络 (ANN) 的智能系统,用于预测影响老年人生活质量的因素. 该系统实现了高准确度,帮助老年人群的医疗保健决策.
科学领域:
- 老年学是指老年学的学科.
- 医疗保健中的人工智能
- 生物医学信息学 生物医学信息学
背景情况:
- 越来越多的老年人患有残疾需要专注关注这一人口群体.
- 有限的研究全面地解决了影响老年人生活质量的身体,精神和疾病相关因素.
- 社会影响 (SA) 受多种因素的影响,这些因素对于了解老年人福祉至关重要.
研究的目的:
- 开发一个智能系统来预测老年人的社会影响 (SA).
- 用人工神经网络 (ANN) 算法研究影响老年人生活质量的因素.
- 促进改善老年人群的健康结果和决策.
主要方法:
- 分析了1156个社会影响 (SA) 和非SA案件.
- 应用统计特征减小来识别关键预测因素.
- 使用FF-BP算法构建和评估具有不同隐藏层神经元 (5,10,15,20) 的ANN模型.
主要成果:
- 确定了25个与社会影响 (SA) 统计相关的因素,P<0.05.
- 性能最好的ANN配置 (25-15-1) 实现了高精度:0.92 (训练),0.86 (测试) 和0.87 (验证).
- 料前向后向传播 (FF-BP) 算法在SA预测中表现出卓越的性能.
结论:
- 开发的智能系统,临床决策支持系统 (CDSS),对于预测SA.至关重要.
- 为老年和医疗保健政策制定者提供有效的决策信息.
- 帮助促进老年人口的生活质量.
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