Artificial Intelligence and Machine Learning for Improving Glycemic Control in Diabetes: Best Practices, Pitfalls, and Opportunities.

Journal: IEEE reviews in biomedical engineering
PMID: 37943654

Abstract

OBJECTIVE: 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.

Authors

  • Peter G Jacobs
  • Pau Herrero
  • Andrea Facchinetti
  • Josep Vehi
    Modeling, Identification and Control Laboratory, Institut d'Informatica i Aplicacions, Universitat de Girona, Girona, Spain.
  • Boris Kovatchev
    University of Virginia Center for Diabetes Technology, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Marc D Breton
    Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA.
  • Ali Cinar
    1 Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA.
  • Konstantina S Nikita
    3 School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou Str., 15780 Zografos, Athens, Greece.
  • Francis J Doyle
    Harvard John A. Paulson School of Engineering and Applied Sciences, Allston, MA, USA.
  • Jorge Bondia
    2 Institut Universitari d'Automàtica i Informàtica Industrial, Universitat Politècnica de València, València, Spain.
  • Tadej Battelino
  • Jessica R Castle
    2 Department of Medicine, Division of Endocrinology, Harold Schnitzer Diabetes Health Center Oregon, Health & Science University, Portland, OR, USA.
  • Konstantia Zarkogianni
  • Rahul Narayan
  • Clara Mosquera-Lopez

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