使用直觉模糊多标准决策的综合方法,以支持帕金森病患者采用技术的分类器选择:算法开发和验证
Miguel Ortiz-Barrios1, Ian Cleland2, Mark Donnelly2
1Department of Productivity and Innovation, Universidad de la Costa CUC, 58th street #55-66, Barranquilla, 080002, Colombia, 57 3007239699.
JMIR rehabilitation and assistive technologies
|October 22, 2024
概括
这项研究引入了一种新的方法来为帕金森病 (PD) 患者选择辅助技术,提高了采用率. 该方法优先考虑结构和适应能力等因素,以便在医疗保健中更好地整合技术.
科学领域:
- 神经科学是一个神经科学.
- 医疗信息学 医疗信息学
- 决策科学 决策科学 决策科学
背景情况:
- 帕金森病 (PD) 是一种主要的神经退行性疾病,给医疗保健带来了重大挑战.
- 辅助技术 (AT) 为PD患者提供了独立生活和远程护理的潜力.
- 可变的AT采用率需要有效分配的预测模型.
研究的目的:
- 提出一种新的混合多标准决策方法来选择分类算法.
- 支持对帕金森病 (PD) 患者的技术采用过程.
主要方法:
- 使用直观模糊分析层次流程 (IF-AHP) 来优先考虑标准和子标准.
- 雇佣了直觉模糊决策试验和评估实验室 (IF-DEMATEL) 来分析因果关系.
- 应用联合妥协解决方案 (CoCoSo) 来对技术采用进行分类.
主要成果:
- 结构 (F5) 具有最高优先级 (重量=0.214);适应性 (F4) 是最有影响力的.
- 确定J48决策树 (A3) 为PD技术采用最合适的算法.
- 拟议的CoCoSo方法与替代方法具有很高的相关性,验证了其准确性.
结论:
- IF-AHP-IF-DEMATEL-CoCoSo方法有效地确定了适合PD患者的辅助技术.
- 该方法考虑了用户采用因素和临床实施的技术特征.
- 这种方法有助于更好地将辅助技术与帕金森病患者的个体需求相匹配.
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