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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Vydané v:	Diabetes research and clinical practice Ročník 191; s. 110029
Hlavní autori:	Cheheltani, Rabee, King, Nicholas, Lee, Suyin, North, Benjamin, Kovarik, Danny, Evans-Molina, Carmella, Leavitt, Nadejda, Dutta, Sanjoy
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Ireland Elsevier B.V 01.09.2022
Predmet:	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
On-line prístup:	Získať plný text
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