Predicting misdiagnosed adult-onset type 1 diabetes using machine learning

It is now understood that almost half of newly diagnosed cases of type 1 diabetes are adult-onset. However, type 1 and type 2 diabetes are difficult to initially distinguish clinically in adults, potentially leading to ineffective care. In this study a machine learning model was developed to identif...

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Bibliographic Details
Published in:	Diabetes research and clinical practice Vol. 191; p. 110029
Main Authors:	Cheheltani, Rabee, King, Nicholas, Lee, Suyin, North, Benjamin, Kovarik, Danny, Evans-Molina, Carmella, Leavitt, Nadejda, Dutta, Sanjoy
Format:	Journal Article
Language:	English
Published:	Ireland Elsevier B.V 01.09.2022
Subjects:	Adult Adult-onset type 1 diabetes Blood Glucose Clinical decision support tool Diabetes Mellitus, Type 1 - diagnosis Diabetes Mellitus, Type 1 - epidemiology Diabetes Mellitus, Type 2 - diagnosis Diabetes Mellitus, Type 2 - drug therapy Diabetes Mellitus, Type 2 - epidemiology Diagnostic Errors Glycated Hemoglobin Humans Machine Learning Misdiagnosis Predictive algorithm Retrospective Studies Misdiagnosis AI Clinical decision support tool Adult-onset type 1 diabetes Predictive algorithm Machine learning
ISSN:	0168-8227, 1872-8227, 1872-8227
Online Access:	Get full text
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