… rules to predict insulin resistant adolescents using both classification and regression tree
(CART) (a … The decision tree is a pictorial representation of a series of if-then rules to predict …

… insulin resistance can be carried out without clinical processes. In this work, insulin resistance
… like logistic regression, CARTs, SVM, LDA, KNN, extra trees classifier. The proposed work …

… The multivariable classification and regression tree (CART) analysis method was used to
identify subgroups of diabetes with differing residual C-peptide levels in patients with newly …

… Since the decision tree nodes can be randomly selected to … upon the gradient boosting
decision tree approach. The basic … gradient boosting decision tree algorithm framework whose …

… tree provides the validity of this result based on selected attributes. This classifier is an excess
tree attribute classifier where each decision tree … At each test node, every decision tree is …

… insulin resistance without having to use invasive medical tests. In this work, insulin resistance
is … to identify a person with a high likelihood of insulin resistance: consisting of age, gender, …

… (TyG) as a marker of insulin resistance (IR) in neonates. TyG … A Decision Tree procedure
(CHAID) was used to classify … birth, justifying the further insulin determination in those neonates. …

… Identification and quantification of insulin resistance requires … Since insulin resistance is a
multi-factorial condition, to … to determine where the insulin-resistance condition is encoded. …

… function is insufficient to overcome the insulin resistance associated with the pregnant state
[… , classification, and regression tree (CART), for the prediction of insulin therapy need in …

… insulin resistance, which appears to play a role in the aetiology of PCOS, since amelioration
of insulin resistance … Furthermore, insulin resistance is proposed to be a major risk factor for …