多学科肺癌治疗的多属性决策框架,考虑到专家愿意改变意见
IEEE transactions on cybernetics
|October 7, 2025
概括
这项研究引入了肺癌治疗的新决策框架,优先考虑专家愿意调整意见. 这种方法提高了治疗计划的接受度,并减少了在多学科治疗过程中不合作的行为.
科学领域:
- 在瘤学瘤学.
- 决策科学 决策科学 决策科学
- 人工智能的人工智能
背景情况:
- 肺癌需要基于复杂的患者数据的个性化治疗策略.
- 多学科治疗 (MDT) 旨在改善患者的治疗结果,但涉及到复杂的决策.
- 现有的多属性多专家决策 (MAMEDM) 模型往往无法解释专家愿意修改他们最初的意见.
研究的目的:
- 开发一个先进的MAMEDM框架,将专家对意见转变的意愿纳入并最大化.
- 改进共识建设过程,在制定最佳肺癌治疗计划方面取得共识.
- 提高临床实践中治疗建议的接受度和有效性.
主要方法:
- 使用语言尺度函数用于预处理专家语言评估.
- 采用模糊的集群算法,根据专家的意见将专家分组.
- 通过网络中心性和专业头来确定子组权重.
- 通过最大限度地提高对意见转变的意愿,汇总专家意见.
- 应用了ORESTE方法来对肺癌治疗选择进行排名.
主要成果:
- 拟议的MAMEDM框架有效地整合了专家们修改评估的意愿.
- 专家意见汇总,考虑转型意愿,导致决策接受度提高.
- 该框架表明,非合作行为在决策过程中的影响减少了.
- 一个关于肺癌治疗的案例研究证实了该框架的有效性.
结论:
- 在复杂的医疗场景 (如肺癌治疗) 中,纳入专家调整意见的意愿对于有效的MAMEDM至关重要.
- 开发的框架为多学科治疗规划提供了更现实的合作方法.
- 这种方法有可能改善共享决策和瘤学患者的治疗结果.
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