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开发一个微专尿风险预测模型:比较2个机器学习算法

Wenyan Long1, Xiaohua Wang1,2, Liqin Lu1

  • 1The Affiliated Hospital of Zunyi Medical University, Zunyi, 563099 China.

Journal of diabetes and metabolic disorders
|November 29, 2024
PubMed
概括

这项研究确定了2型糖尿病中微albuminuria的关键预测因子,开发了风险预测的随机森林模型. 糖化血红蛋白,中性粒细胞对淋巴细胞的比率和25-氧维生素D是最重要的,维生素D具有保护作用.

关键词:
在BP神经网络中,神经网络糖尿病是一种糖尿病.这些因素是因素.机器学习是机器学习.微专辑蛋白尿症是什么意思预测模型的预测模型.随机的森林 随机的森林这就是 SHAP SHAP 的意思.

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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