用机器学习框架评估患有刺激性肠综合征的患者自我报告的执行功能
Astri J Lundervold1, Eline M R Hillestad2,3, Gülen Arslan Lied2,3
1Department of Biological and Medical Psychology, University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway.
刺激性肠综合征 (IBS) 患者表现出显著的执行功能 (EF) 问题,特别是工作记忆. 这些发现表明,EF评估和工作记忆干预对于管理IBS至关重要.
科学领域:
- 神经科学是一个神经科学.
- 胃肠病学 胃肠病学
- 心理学 心理学 心理学
背景情况:
- 刺激性肠综合征 (IBS) 是一种肠-大脑相互作用障碍 (DGBI).
- 执行功能 (EF) 是关键的认知过程.
- IBS和EF赤字之间的关系需要进一步调查.
研究的目的:
- 探索IBS患者的执行功能 (EF) 问题.
- 确定导致IBS的最重要的认知特征.
- 开发一种机器学习模型,基于EF对IBS患者进行分类.
主要方法:
- 44名IBS患者和22名健康对照 (HCs) 完成了执行功能的行为评级清单 (BRIEF-A).
- 机器学习 (PyCaret 3.0,XGBoost) 用于分析EF特征和分类组.
- 模型的稳定性在未见的数据集上得到验证.
主要成果:
- IBS患者在工作记忆,启动,认知灵活性和情绪控制方面报告了明显更严重的EF问题.
- 机器学习模型将工作记忆,计划和情绪控制确定为EF的关键特征.
- 在XGBoost模型的使用中,在对IBS患者进行分类时,获得了85%的准确性.
结论:
- 执行功能 (EF) 缺陷,特别是工作记忆,在IBS患者中很普遍.
- 环境环境评估应纳入IBS诊断程序.
- 工作记忆干预可能是IBS的有价值的治疗目标.
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