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机器学习使得基于糖尿病足部感染患者不良情绪的风险因素构建名录

Heng Du¹, Baoqin Meng², Shixing Ma³

¹Medical Department and Outpatient Service of Geriatric and Endocrinology Department, Baoji Central Hospital Baoji 721008, Shaanxi, China.

American journal of translational research

|September 15, 2025

概括

这项研究确定了糖尿病足部感染患者情绪障碍的关键风险因素. 开发了一个名录模型来预测不良情绪,帮助临床评估和干预.

科学领域:

医学研究医学研究
临床心理学临床心理学
糖尿病学糖尿病学

背景情况:

糖尿病足部感染与严重的心理痛苦有关.
准确预测情绪障碍对于及时干预至关重要.

研究的目的:

为了确定患有糖尿病足部感染的患者情绪障碍的危险因素.
开发和验证一个用于预测情绪障碍的诺莫格拉姆模型.

主要方法:

对313名糖尿病足部感染患者的回顾性分析.
机器学习模型和物流回归用于识别风险因素.
使用ROC曲线,校准曲线和DCA进行诺摩图构造和验证.

主要成果:

瓦格纳分类,并发症,HbA1c,性别和糖尿病史被确定为独立的风险因素.
在测试组中,名图显示出高预测准确度 (AUC=0.829).
该模型通过校准和DCA显示稳定性和临床相关性,并通过外部验证证实.

结论:

一种名ogram模型有效地预测糖尿病足部感染患者的情绪障碍.
机器学习确定了关键的风险因素,提高了预测准确度.
诺姆图表是临床评估和有针对性的干预措施的宝贵工具.

关键词:

回归建模的回归建模.负面的情绪负面的情绪糖尿病足部感染糖尿病足部感染预测建模预测建模有关风险因素的风险因素.

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