This paper is in the following e-collection/theme issue:

Diabetes Technology Around the World (25) Machine Learning (1694)

Published on in Vol 3, No 4 (2018): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10212, first published .
Prediction of Glucose Metabolism Disorder Risk Using a Machine Learning Algorithm: Pilot Study

Prediction of Glucose Metabolism Disorder Risk Using a Machine Learning Algorithm: Pilot Study

Prediction of Glucose Metabolism Disorder Risk Using a Machine Learning Algorithm: Pilot Study

Authors of this article:

Katsutoshi Maeta1 Author Orcid Image ;   Yu Nishiyama1 Author Orcid Image ;   Kazutoshi Fujibayashi2 Author Orcid Image ;   Toshiaki Gunji3 Author Orcid Image ;   Noriko Sasabe3 Author Orcid Image ;   Kimiko Iijima3 Author Orcid Image ;   Toshio Naito2 Author Orcid Image
Article Authors Cited by (21) Tweetations (1) Metrics

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  12. Haneef R, Tijhuis M, Thiébaut R, Májek O, Pristaš I, Tolonen H, Gallay A. Methodological guidelines to estimate population-based health indicators using linked data and/or machine learning techniques. Archives of Public Health 2022;80(1) View
  13. Homma Y, Ito S, Zhuang X, Baba T, Fujibayashi K, Kaneko K, Nishiyama Y, Ishijima M. Artificial intelligence for distinguishment of hammering sound in total hip arthroplasty. Scientific Reports 2022;12(1) View
  14. Schwartz J, Tseng E, Maruthur N, Rouhizadeh M. Identification of Prediabetes Discussions in Unstructured Clinical Documentation: Validation of a Natural Language Processing Algorithm. JMIR Medical Informatics 2022;10(2):e29803 View
  15. Shrestha B, Alsadoon A, Prasad P, Al-Naymat G, Al-Dala’in T, Rashid T, Alsadoon O. Enhancing the prediction of type 2 diabetes mellitus using sparse balanced SVM. Multimedia Tools and Applications 2022;81(27):38945 View
  16. Mohammadnezhad K, Sahebi M, Alatab S, Sadjadi A. Modeling Epidemiology Data with Machine Learning Technique to Detect Risk Factors for Gastric Cancer. Journal of Gastrointestinal Cancer 2024;55(1):287 View
  17. Orășeanu A, Brisc M, Maghiar O, Popa H, Brisc C, Șolea S, Maghiar T, Brisc C. Landscape of Innovative Methods for Early Diagnosis of Gastric Cancer: A Systematic Review. Diagnostics 2023;13(24):3608 View
  18. Owess M, Owda A, Owda M, Massad S. Supervised Machine Learning-Based Models for Predicting Raised Blood Sugar. International Journal of Environmental Research and Public Health 2024;21(7):840 View
  19. Zhang X, Yao W, Wang D, Hu W, Zhang G, Zhang Y. Development and Validation of Machine Learning Models for Identifying Prediabetes and Diabetes in Normoglycemia. Diabetes/Metabolism Research and Reviews 2024;40(8) View
  20. 金岡 丈, 今釜 崇, 岡﨑 朋, 松木 佑, 川上 武, 山﨑 和, 坂井 孝. 機械学習によるステムサイズ予測モデルの精度検証. Orthopedics & Traumatology 2024;73(3):452 View

Conference Proceedings

  1. Zhou H, Wang J. Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine Science. Design of Intelligent Elderly Care Service System Combined With the Medical Care and Elderly Care Based on IoT: Study on Intelligent Elderly Care Service System Service Model and Hierarchical Architecture Based on IoT View