机器学习
可解释性
人工智能
计算机科学
个性化
领域(数学)
血糖性
糖尿病
医学
数学
内分泌学
万维网
纯数学
作者
Peter G. Jacobs,Pau Herrero,Andrea Facchinetti,Josep Vehı́,Boris Kovatchev,Marc D. Breton,Ali Çιnar,Konstantina S. Nikita,Francis J. Doyle,Jorge Bondía,Tadej Battelino,Jessica R. Castle,Konstantia Zarkogianni,Rahul Narayan,Clara Mosquera-Lopez
标识
DOI:10.1109/rbme.2023.3331297
摘要
Artificial intelligence and machine learning are transforming many fields including medicine. In diabetes, robust biosensing technologies and automated insulin delivery therapies have created a substantial opportunity to improve health. While the number of manuscripts addressing the topic of applying machine learning to diabetes has grown in recent years, there has been a lack of consistency in the methods, metrics, and data used to train and evaluate these algorithms. This manuscript provides consensus guidelines for machine learning practitioners in the field of diabetes, including best practice recommended approaches and warnings about pitfalls to avoid.
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