1233-P: Prediction of Type 2 Diabetes Occurrence Using Machine Learning Model

Prediction of type 2 diabetes (T2D) occurrence allows a person at risk to take preventive actions that can prevent or delay the progression of the disease. In this study, we aim to develop a machine learning (ML) model to predict T2D occurrence in the year Y+1 using the variables in the year Y. The...

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Veröffentlicht in:	Diabetes (New York, N.Y.) N.Y.), 2020-06, Vol.69 (Supplement_1)
Hauptverfasser:	DEBERNEH, HENOCK M., KIM, INTAEK, PARK, JAE HYUN, CHA, EUNSEOK, JOUNG, KYONG HYE, LEE, JONG SEON, LIM, DONG SEOK
Format:	Artikel
Sprache:	eng
Schlagworte:	Body mass index Diabetes Diabetes mellitus (non-insulin dependent) Electronic medical records Guanosine triphosphate Learning algorithms Machine learning Physical activity Prediction models Triglycerides Uric acid
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