Insulin resistance is an early-stage deterioration of Type 2 diabetes. Identification and quantification of insulin resistance requires specific blood tests; however, the triglyceride-glucose (TyG) index can provide a surrogate assessment from routine Electronic Health Record (EHR) data. Since insulin resistance is a multi-factorial condition, to improve its characterisation, this study aims to discover non-trivial clinical factors in EHR data to determine where the insulin-resistance condition is encoded.
TyG-er: An ensemble Regression Forest approach for identification of clinical factors related to insulin resistance condition using Electronic Health Records / Bernardini, M.; Morettini, M.; Romeo, L.; Frontoni, E.; Burattini, L.. - In: COMPUTERS IN BIOLOGY AND MEDICINE. - ISSN 0010-4825. - ELETTRONICO. - 112:103358(2019), pp. 1-8. [10.1016/j.compbiomed.2019.103358]
TyG-er: An ensemble Regression Forest approach for identification of clinical factors related to insulin resistance condition using Electronic Health Records
Bernardini M.;Morettini M.;Romeo L.;Frontoni E.
;Burattini L.
2019-01-01
Abstract
Insulin resistance is an early-stage deterioration of Type 2 diabetes. Identification and quantification of insulin resistance requires specific blood tests; however, the triglyceride-glucose (TyG) index can provide a surrogate assessment from routine Electronic Health Record (EHR) data. Since insulin resistance is a multi-factorial condition, to improve its characterisation, this study aims to discover non-trivial clinical factors in EHR data to determine where the insulin-resistance condition is encoded.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
