Skip Navigation
Skip to contents

Diabetes Metab J : Diabetes & Metabolism Journal

Search
OPEN ACCESS

Author index

Page Path
HOME > Browse > Author index
Search
Kazuya Fujihara 1 Article
Drug/Regimen
Machine Learning Approach to Drug Treatment Strategy for Diabetes Care
Kazuya Fujihara, Hirohito Sone
Diabetes Metab J. 2023;47(3):325-332.   Published online January 12, 2023
DOI: https://doi.org/10.4093/dmj.2022.0349
  • 65,535 View
  • 243 Download
  • 1 Web of Science
  • 2 Crossref
AbstractAbstract PDFPubReader   ePub   
Globally, the number of people with diabetes mellitus has quadrupled in the past three decades, and approximately one in 11 adults worldwide have diabetes mellitus. Since both microvascular and macrovascular diseases in patients with diabetes predispose them to a lower quality of life as well as higher rates of mortality, managing blood glucose levels is of clinical relevance in diabetes care. Many classes of antihyperglycemic drugs are currently approved to treat hyperglycemia in patients with type 2 diabetes mellitus, with several new drugs having been developed during the last decade. Diabetes-related complications have been reduced substantially worldwide. Prioritization of therapeutic agents varies according to national guidelines. However, since the characteristics of participants in clinical trials differ from patients in actual clinical practice, it is difficult to apply the results of such trials to clinical practice. Machine learning approaches became highly topical issues in medicine along with rapid technological innovations in the fields of information and communication in the 1990s. However, adopting these technologies to support decision-making regarding drug treatment strategies for diabetes care has been slow. This review summarizes data from recent studies on the choice of drugs for type 2 diabetes mellitus focusing on machine learning approaches.

Citations

Citations to this article as recorded by  
  • Exploring antioxidant activities and inhibitory effects against α‐amylase and α‐glucosidase of Elaeocarpus braceanus fruits: insights into mechanisms by molecular docking and molecular dynamics
    Hong Li, Yuanyue Zhang, Zhijia Liu, Chaofan Guo, Maurizio Battino, Shengbao Cai, Junjie Yi
    International Journal of Food Science & Technology.2024; 59(1): 343.     CrossRef
  • 3D Convolutional Neural Networks for Predicting Protein Structure for Improved Drug Recommendation
    Pokkuluri Kiran Sree, SSSN Usha Devi N
    EAI Endorsed Transactions on Pervasive Health and Technology.2024;[Epub]     CrossRef

Diabetes Metab J : Diabetes & Metabolism Journal