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基于机器学习的模型的开发和外部验证,以预测糖尿病人群中糖尿病足的糖尿病足

Yanji Zhang¹, Yingying Tian², Yang Jian¹

¹Department of Burns and Plastic Surgery, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.

Frontiers in endocrinology

|December 31, 2025

概括

机器学习模型在预测糖尿病足 (DFU) 风险方面表现有前途. 随机森林模型在识别早期干预的高风险个体方面表现出最高的准确性.

科学领域:

医疗信息学医疗信息学
医疗保健中的人工智能
糖尿病管理糖尿病管理

背景情况:

糖尿病足 (DFU) 是一种严重的糖尿病并发症,影响生活质量和死亡率.
早期识别高风险个体对于有效的干预和预防策略至关重要.

研究的目的:

系统评估机器学习 (ML) 方法的诊断准确性,以预测糖尿病患者的DFU风险.
为了比较各种ML模型在识别患DFU风险的个人的表现.

主要方法:

遵守关于透明报告的TRIPOD+AI指南.
使用NHANES 1999-2004数据进行模型培训 (物流回归,KNN,RF,XGBoost,SVM).
对单独的临床数据集进行外部验证,以评估可概括性.

主要成果:

随机森林 (RF) 模型在NHANES数据集上实现了0.81的最高AUC.
在外部验证中,RF也表现出优异的性能,AUC为0.79.
其他模型,如XGBoost (0.76) 和SVM (0.72),也表现出良好的预测能力.

结论:

机器学习模型对预测DFU在不同人群中的风险具有很好的潜力.
模型性能可能因地区而异,因此需要对特定患者群体进行仔细的算法选择.
结果支持对这些预测模型进行进一步的临床评估,用于DFU管理.

关键词:

尼汉斯 (NHANES) 是一个名人.糖尿病足部糖尿病足部诊断诊断诊断诊断诊断诊断通过外部验证.机器学习是机器学习.

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Diabetic Foot Ulcer

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Definition A diabetic foot ulcer (DFU) is a chronic, non-healing wound that develops in individuals with diabetes. It typically occurs on pressure-bearing areas such as the heel, metatarsal heads, or hallux, and carries a high risk of infection and amputation.Pathophysiology • The development of DFUs can be explained by four interconnected mechanisms: neuropathy, ischemia, infection, and impaired wound healing. • Neuropathy is the most common factor. Sensory neuropathy reduces pain perception,...