Detrended Fluctuation Analysis in the prediction of type 2 diabetes mellitus in patients at risk: Model optimization and comparison with other metrics

Complexity analysis of glucose time series with Detrended Fluctuation Analysis (DFA) has been proved to be useful for the prediction of type 2 diabetes mellitus (T2DM) development. We propose a modified DFA algorithm, review some of its characteristics and compare it with other metrics derived from...

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Bibliographic Details
Published in:	PloS one Vol. 14; no. 12; p. e0225817
Main Authors:	Colás, Ana, Vigil, Luis, Vargas, Borja, Cuesta–Frau, David, Varela, Manuel
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 18.12.2019 Public Library of Science (PLoS)
Subjects:	Adolescent Adult Aged Aged, 80 and over Algorithms Biology and Life Sciences Blood Glucose - analysis Circadian rhythms Coefficient of variation Datasets as Topic Diabetes Diabetes mellitus Diabetes mellitus (non-insulin dependent) Diabetes Mellitus, Type 2 - diagnosis Engineering and Technology Fasting Female Glucose Glucose tolerance Hospitals Humans Hypertension Integration Internal medicine Interpolation Male Mathematical analysis Medicine Medicine and Health Sciences Middle Aged Noise prediction Optimization Patients Physical Sciences Prediabetic state Principal components analysis Regression analysis Research and Analysis Methods Risk Factors Segments Time series Type 2 diabetes White noise Windows (intervals) Young Adult Borja Spain Spain
ISSN:	1932-6203, 1932-6203
Online Access:	Get full text
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