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당뇨병 및 내분비질환 분야 머신러닝 활용

Machine Learning Application in Diabetes and Endocrine Disorders

Journal of Korean Diabetes 2020년 21권 3호 p.130 ~ 139
Hong Nam-Ki, Park Hea-Jeong, 이유미,
소속 상세정보
 ( Hong Nam-Ki ) - Yonsei University College of Medicine Department of Internal Medicine Division of Endocrinology and Metabolism
 ( Park Hea-Jeong ) - Yonsei University College of Medicine Department of Internal Medicine Division of Endocrinology and Metabolism
이유미 ( Rhee Yu-Mie ) - Yonsei University College of Medicine Department of Internal Medicine Division of Endocrinology and Metabolism

Abstract


Recently, machine learning (ML) applications have received attention in diabetes and metabolism research. This review briefly provides the basic concepts of ML and specific topics in diabetes research. Exemplary studies are reviewed to provide an overview of the methodology, main findings, limitations, and future research directions for ML-based studies. Well-defined, testable study hypotheses that stem from unmet clinical needs are always the first prerequisite for successful deployment of an MLbased approach to clinical scene. The management of data quality with enough quantity and active collaboration with ML engineers can enhance the ML development process. The interpretable highperformance
ML models beyond the black-box nature of some ML principles can be one of the future goals expected by ML and artificial intelligence in the diabetes research and clinical practice settings that is beyond hype. Most importantly, endocrinologists should play a central role as domain experts who have clinical expertise and scientific rigor, for properly generating, refining, analyzing, and interpreting data by successfully integrating ML models into clinical research.

키워드

Artificial intelligence; Deep learning; Diabetes mellitus; Machine learning; Metabolism

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