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Updated: Jan 9, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

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探索可解释的机器学习来预测和解释田纳西州成年人中自我报告的糖尿病:来自2023年行为风险因素监测系统 (BRFSS) 的见解

Mustapha Aliyu Muhammad1, Jamilu Sani2, Mohamed Mustaf Ahmed3

  • 1Biostatistics and Epidemiology Department, College of Public Health, East Tennessee State University, Johnson City, Tennessee, USA.

Journal of primary care & community health
|December 1, 2025
PubMed
概括

机器学习,特别是渐变增强,有效地预测了田纳西州的糖尿病风险. 关键因素包括高血压,肥胖和不活动,突出了针对性公共卫生干预的机会.

关键词:
行为风险因素监测系统 (BRFSS)在SHAP分析中,我们分析了SHAP.糖尿病 糖尿病患者 糖尿病患者可以解释的人工智能AI机器学习是机器学习.人口监视人口监视人口监视公共卫生信息学 公共卫生信息学风险预测风险预测

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