Keyphrases
End-stage Renal Disease
100%
Artificial Intelligence Algorithm
100%
Newly Diagnosed Type 2 Diabetes Mellitus
100%
Type 2 Diabetes Mellitus (T2DM)
50%
Type 2 Diabetes Mellitus Patients
50%
Clinical Features
50%
Machine Learning Models
50%
Gradient Boosting Decision Tree
50%
Clinical Setting
25%
Predictive Models
25%
High-sensitivity C-reactive Protein (hs-CRP)
25%
Logistic Regression
25%
Female Gender
25%
Intervention Strategies
25%
Area under the Receiver Operating Characteristic Curve
25%
Discriminative Ability
25%
Random Forest
25%
Diabetic Nephropathy
25%
Protein Spots
25%
Best Model
25%
Health Systems
25%
AUC Value
25%
Kidney Function
25%
Patient Experience
25%
XGBoost
25%
Extreme Gradient Boosting(XGBoost)
25%
Tree Boosting
25%
Risk Assessment Tool
25%
Long-run Risk
25%
Clinical High Risk
25%
Shapley Additive Explanations
25%
Summary Plots
25%
Baseline Serum Creatinine
25%
Protein-to-creatinine Ratio
25%
XGBoost Model
25%
Patient-centered Intervention
25%
Machine Learning Prediction
25%
Light Gradient Boosting Machine
25%
Extra Trees
25%
Biochemistry, Genetics and Molecular Biology
Decision Trees
100%
Artificial Intelligence
100%
Random Forest
50%
Kidney Function
50%
C-Reactive Protein
50%
Creatinine Blood Level
50%
Protein Urine Level
50%
Creatinine
50%
Immunology and Microbiology
Decision Trees
100%
Artificial Intelligence
100%
Kidney Function
50%
C-Reactive Protein
50%
Creatinine Blood Level
50%
Protein Urine Level
50%
Random Forest
50%
Mathematics
Decision Tree
100%
Characteristic Curve
50%
Training Set
50%
Predictive Model
50%
Logistic Regression
50%
Testing Set
50%
Light Gradient
50%
Medicine and Dentistry
Maturity Onset Diabetes of the Young
100%
End Stage Renal Disease
100%
Clinical Feature
40%
Creatinine
40%
Logistic Regression Analysis
20%
Diabetic Nephropathy
20%
Kidney Function
20%
C Reactive Protein
20%
Patient Experience
20%
Neuroscience
Diabetes Mellitus
100%
Creatinine
33%
C-Reactive Protein
16%