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慢性呼吸系统疾病中的认知,情感和呼吸系统概况之间的相互作用:一个集群分析方法
Iulian-Laurențiu Buican1,2, Victor Gheorman3, Ion Udriştoiu3
1U.M.F. Doctoral School Craiova, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania.
Diagnostics (Basel, Switzerland)
|June 19, 2024
概括
机器学习确定了慢性呼吸系统疾病的三个患者群,揭示了呼吸系统问题与认知/情感健康之间的联系. 根据这些概况进行量身定制的治疗可以改善患者的治疗结果和日常功能.
科学领域:
- 肺部病理学 肺部病理学
- 神经科学是一个神经科学.
- 精神病学是一个精神病学.
背景情况:
- 慢性呼吸道疾病,如喘和COPD显著影响患者的认知和情感状态.
- 了解这些相互关系对于全面的患者管理至关重要.
研究的目的:
- 研究慢性呼吸系统疾病患者的认知,情感和呼吸系统变量之间的相互关系.
- 通过机器学习来识别不同的患者群体,以实现个性化的治疗策略.
主要方法:
- 采用基于机器学习的聚类技术,对100名住院喘和COPD患者的数据进行分析.
- 使用标准化仪器:mMRC,CAT,螺旋计,MMSE,MoCA和汉密尔顿焦虑和抑郁量表.
主要成果:
- 划分了三个不同的集群:中度,严重和稳定的认知呼吸.
- 在集群中发现呼吸道症状严重程度和认知/情感状况之间的显著相关性.
结论:
- 强调COPD和喘综合个性化治疗方法的好处.
- 倡导基于认知,情感和呼吸系统相互作用的治疗定制,以提高患者的生活质量.
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