Machine learning in precision diabetes care and cardiovascular risk prediction

Cardiovascular Diabetology

Review

Evangelos K. Oikonomou¹  Rohan Khera² 

[1] Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA;Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA;Section of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA;Section of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, USA;Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, 195 Church St, 6th floor, 06510, New Haven, CT, USA;

关键词: Machine learning;    Artificial intelligence;    Prediction;    Personalized medicine;    Digital health;    Diabetes;    Cardiovascular disease;   

DOI  :  10.1186/s12933-023-01985-3

 received in 2023-07-25, accepted in 2023-09-07,  发布年份 2023

来源: Springer

【 摘 要 】

Artificial intelligence and machine learning are driving a paradigm shift in medicine, promising data-driven, personalized solutions for managing diabetes and the excess cardiovascular risk it poses. In this comprehensive review of machine learning applications in the care of patients with diabetes at increased cardiovascular risk, we offer a broad overview of various data-driven methods and how they may be leveraged in developing predictive models for personalized care. We review existing as well as expected artificial intelligence solutions in the context of diagnosis, prognostication, phenotyping, and treatment of diabetes and its cardiovascular complications. In addition to discussing the key properties of such models that enable their successful application in complex risk prediction, we define challenges that arise from their misuse and the role of methodological standards in overcoming these limitations. We also identify key issues in equity and bias mitigation in healthcare and discuss how the current regulatory framework should ensure the efficacy and safety of medical artificial intelligence products in transforming cardiovascular care and outcomes in diabetes.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

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