01418nas a2200445   4500000000100000000000100001000000100002008004100003653001100044653004400055653002400099653001900123653002300142653004300165653004900208653004000257653005600297653006100353653002200414653001800436653003000454653003100484653003600515653002100551653003500572653002400607653002000631100002600651700001400677700001500691700001800706700001300724700001500737700001400752245016200766250001500928300000800943490000700951020001400958       2023                            d10aHumans10a*Diabetes Mellitus, Type 2/drug therapy10aGlycated Hemoglobin10aCohort Studies10aPrecision medicine10aDipeptidyl Peptidase 4/therapeutic use10aSodium-Glucose Transporter 2/therapeutic use10aHypoglycemic Agents/therapeutic use10a*Dipeptidyl-Peptidase IV Inhibitors/therapeutic use10a*Sodium-Glucose Transporter 2 Inhibitors/therapeutic use10aTreatment Outcome10aCausal forest10aCounterfactual prediction10aGeneralized random forests10aHeterogeneous treatment effects10amachine learning10aTreatment effect heterogeneity10aTreatment selection10aType 2 diabetes1 aA. Venkatasubramaniam1 aB. Mateen1 aB. Shields1 aA. Hattersley1 aA. Jones1 aS. Vollmer1 aJ. Dennis00aComparison of causal forest and regression-based approaches to evaluate treatment effect heterogeneity: an application for type 2 diabetes precision medicine  a2023/06/17  a1100 v23  a1472-6947