A Significance Assessment of Diabetes Diagnostic Biomarkers Using Machine Learning
Suominen Hanna; Lenskiy Artem; Hossain Md Zakir; Cui Ran; Nolan Christopher J; Daskalaki Elena
A Significance Assessment of Diabetes Diagnostic Biomarkers Using Machine Learning
Suominen Hanna
Lenskiy Artem
Hossain Md Zakir
Cui Ran
Nolan Christopher J
Daskalaki Elena
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2022091258503
https://urn.fi/URN:NBN:fi-fe2022091258503
Tiivistelmä
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.
Kokoelmat
- Rinnakkaistallenteet [19207]