Journal: Journal of Diabetes Science and Technology

Article Title: Reverse Engineering and Evaluation of Prediction Models for Progression to Type 2 Diabetes

doi: 10.1177/1932296815620200

Figure Lengend Snippet: Flow diagram describing restriction criteria for analytical study population applied to Humedica electronic health records data sample, 2007-2012. BG, blood glucose; IDN, integrated delivery network; UACR, urinary albumin to creatinine ratio.

Article Snippet: Data for non-IDN patients were set aside and used as a testing set for prediction models constructed within the study population. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 1. caption a7 Flow diagram describing restriction criteria for analytical study population applied to Humedica electronic health records data sample, 2007-2012.

Techniques:

Journal: Journal of Diabetes Science and Technology

Article Title: Reverse Engineering and Evaluation of Prediction Models for Progression to Type 2 Diabetes

doi: 10.1177/1932296815620200

Figure Lengend Snippet: Distributions of Selected Baseline Characteristics Among the Primary Study Population (N = 24 331), and Proportion Progressing to Type 2 Diabetes, Humedica Electronic Health Records Data Sample, 2007-2012.

Article Snippet: Data for non-IDN patients were set aside and used as a testing set for prediction models constructed within the study population. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 1. caption a7 Flow diagram describing restriction criteria for analytical study population applied to Humedica electronic health records data sample, 2007-2012.

Techniques:

Journal: Journal of Diabetes Science and Technology

Article Title: Reverse Engineering and Evaluation of Prediction Models for Progression to Type 2 Diabetes

doi: 10.1177/1932296815620200

Figure Lengend Snippet: Variable Selection Frequency and Effect Estimates for Selected Patient Factors Across 3 Models of Progression to Prediabetes or T2D, Humedica Electronic Health Records Data Sample, 2007-2012.

Article Snippet: Data for non-IDN patients were set aside and used as a testing set for prediction models constructed within the study population. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 1. caption a7 Flow diagram describing restriction criteria for analytical study population applied to Humedica electronic health records data sample, 2007-2012.

Techniques: Selection

Journal: Journal of Diabetes Science and Technology

Article Title: Reverse Engineering and Evaluation of Prediction Models for Progression to Type 2 Diabetes

doi: 10.1177/1932296815620200

Figure Lengend Snippet: Kaplan–Meier plots for time to T2D by selected (potentially modifiable) patient factors: baseline blood glucose measures, triglycerides, systolic blood pressure, and history of lipid disorders, Humedica electronic health records data sample, 2007-2012.

Article Snippet: Data for non-IDN patients were set aside and used as a testing set for prediction models constructed within the study population. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 1. caption a7 Flow diagram describing restriction criteria for analytical study population applied to Humedica electronic health records data sample, 2007-2012.

Techniques:

Journal: Journal of Diabetes Science and Technology

Article Title: Reverse Engineering and Evaluation of Prediction Models for Progression to Type 2 Diabetes

doi: 10.1177/1932296815620200

Figure Lengend Snippet: Receiver operating characteristic curves for accuracy of the REFS ensemble in predicting progression to diabetes (from normoglycemia) in the training and testing data sets, Humedica electronic health records data sample, 2007-2012.

Article Snippet: Data for non-IDN patients were set aside and used as a testing set for prediction models constructed within the study population. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 1. caption a7 Flow diagram describing restriction criteria for analytical study population applied to Humedica electronic health records data sample, 2007-2012.

Techniques:

Journal: Journal of Diabetes Science and Technology

Article Title: Reverse Engineering and Evaluation of Prediction Models for Progression to Type 2 Diabetes

doi: 10.1177/1932296815620200

Figure Lengend Snippet: Individual 3.5-year risk of diabetes for 2 selected patients, Humedica electronic health records data sample, 2007-2012.

Article Snippet: Data for non-IDN patients were set aside and used as a testing set for prediction models constructed within the study population. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 1. caption a7 Flow diagram describing restriction criteria for analytical study population applied to Humedica electronic health records data sample, 2007-2012.

Techniques:

Journal: Journal of Diabetes Science and Technology

Article Title: Reverse Engineering and Evaluation of Prediction Models for Progression to Type 2 Diabetes

doi: 10.1177/1932296815620200

Figure Lengend Snippet: Kaplan–Meier plots for time to prediabetes by selected patient factors, Humedica electronic health records data sample, 2007-2012.

Article Snippet: Data for non-IDN patients were set aside and used as a testing set for prediction models constructed within the study population. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 1. caption a7 Flow diagram describing restriction criteria for analytical study population applied to Humedica electronic health records data sample, 2007-2012.

Techniques: