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Association between machine learning-assisted heavy metal exposures and diabetic kidney disease: A Cross-Sectional Survey and Mendelian Randomization Analysis

2024-02-27

Abstract excerpt

<title>Abstract</title> <p><bold>Background & objective: </bold>Heavy metals, ubiquitous in the environment, pose a global public health concern. The correlation between these and diabetic kidney disease (DKD) remains unclear. <bold>Methods</bold>: We analyzed data from the NHANES (2005–2020), using machine learning, and cross-sectional survey. Our study also involved a bidirectional two-sample Mendelian randomiz...

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Literature Corpus work
05ebcb2b-6001-5a94-8cf2-dcbe8002e9b6
DOI
10.21203/rs.3.rs-3982384/v1
Open publication

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Association between machine learning-assisted heavy metal exposures and diabetic kidney disease: A Cross-Sectional Survey and Mendelian Randomization AnalysisDOI 10.21203/rs.3.rs-3982384/v1
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