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A Significance Assessment of Diabetes Diagnostic Biomarkers Using Machine Learning
Ran Cui, Elena Daskalaki, Md Zakir Hossain, Artem Lenskiy, Christopher J Nolan, Hanna Suominen
36 - 38
10.3233/SHTI210657
Research Article
Studies in Health Technology and Informatics
Volume 284: Nurses and Midwives in the Digital Age
Abstract

Diabetes can be diagnosed by either Fasting Plasma Glucose or Hemoglobin A1c. The aim of our study was to explore the differences between the two criteria through the development of a machine learning based diabetes diagnostic algorithm and analysing the predictive contribution of each input biomarker. Our study concludes that fasting insulin is predictive of diabetes defined by FPG, but not by HbA1c. Besides, 28 other fasting blood biomarkers were not significant predictors of diabetes.

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