@inproceedings{530cfe5a07524b819ab9f839e23f477a,
title = "A Significance Assessment of Diabetes Diagnostic Biomarkers Using Machine Learning",
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.",
keywords = "Diabetes biomarkers, feature importance, machine learning",
author = "Ran Cui and Elena Daskalaki and Hossain, {Md Zakir} and Artem Lenskiy and Nolan, {Christopher J.} and Hanna Suominen",
note = "Publisher Copyright: {\textcopyright} 2021 International Medical Informatics Association (IMIA) and IOS Press.; 15th International Congress in Nursing Informatics: Nurses and Midwives in the Digital Age, NI 2021 ; Conference date: 23-08-2021 Through 02-09-2021",
year = "2021",
month = dec,
day = "15",
doi = "10.3233/SHTI210657",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "36--38",
editor = "Michelle Honey and Charlene Ronquillo and Ting-Ting Lee and Lucy Westbrooke",
booktitle = "Nurses and Midwives in the Digital Age - Selected Papers, Posters and Panels from the 15th International Congress in Nursing Informatics",
address = "Netherlands",
}