Logistic regression analysis for prediction of new-onset type 2 diabetes.

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https://figshare.com/articles/dataset/Logistic_regression_analysis_for_prediction_of_new-onset_type_2_diabetes_/5200609 数据链接链接失效反馈

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Logistic regression analysis for prediction of new-onset type 2 diabetes.

创建时间：

2017-07-13

Ghai et al. T2DM METSIM_Suppl_Figure1.tiff

2型糖尿病预测

环状RNA生物标志物

Supplemental Data from Ghai et al. in prep. "Circulating RNAs as predictive markers for the progression to type 2 diabetes in prediabetic patients"

Figshare2018-10-15 更新70

Table3_A framework towards digital twins for type 2 diabetes.xlsx

2型糖尿病预测

数字孪生医疗

IntroductionA digital twin is a virtual representation of a patient's disease, facilitating real-time monitoring, analysis, and simulation. This enables the prediction of disease progression, optimiza

NIAID Data Ecosystem30

Metabolites used in prediction of incident T2D with average P-value, false discovery rate (FDR), odds ratio (OR) and 95% confidence interval (95% CI) from the pairwise comparisons of the NGT and IGT groups to the T2D group.

代谢物生物标志物

2型糖尿病预测

NIAID Data Ecosystem20

Additional file 2 of Specific triacylglycerol, diacylglycerol, and lyso-phosphatidylcholine species for the prediction of type 2 diabetes: a ~ 16-year prospective study in Chinese

脂质组学生物标志物

2型糖尿病预测

Additional file 2: Table S1. Stepwise model selection coefficients and Wald-Z tests. Table S2. List of measured lipid species. Table S3. Weighted gene co-expression network analysis module components.

Figshare2024-02-05 更新40

DiaHealth: A Bangladeshi Dataset for Type 2 Diabetes Prediction

2型糖尿病预测

医疗健康数据

his dataset provides comprehensive information on 5,437 patients, including 14 independent attributes such as demographics, clinical parameters, and medical history. Key features include age, gender,

Mendeley Data20

Logistic regression analysis for prediction of new-onset type 2 diabetes.

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