期刊文献+

Machine Learning Models in Type 2 Diabetes Risk Prediction:Results from a Cross-sectional Retrospective Study in Chinese Adults 被引量:4

下载PDF
导出
摘要 Type 2 diabetes mellitus (T2DM) has become a prevalent health problem in China,especially in urban areas.Early prevention strategies are needed to reduce the associated mortality and morbidity.We applied the combination of rules and different machine learning techniques to assess the risk of development of T2DM in an urban Chinese adult population.A retrospective analysis was performed on 8000 people with non-diabetes and 3845 people with T2DM in Nanjing.Multilayer Perceptron (MLP),AdaBoost (AD),Trees Random Forest (TRF),Support Vector Machine (SVM),and Gradient Tree Boosting (GTB) machine learning techniques with 10 cross validation methods were used with the proposed model for the prediction of the risk of development of T2DM.The performance of these models was evaluated with accuracy,precision,sensitivity,specificity,and area under receiver operating characteristic (ROC) curve (AUC).After comparison,the prediction accuracy of the different five machine models was 0.87,0.86,0.86,0.86 and 0.86 respectively.The combination model using the same voting weight of each component was built on T2DM,which was performed better than individual models.The findings indicate that,combining machine learning models could provide an accurate assessment model for T2DM risk prediction.
出处 《Current Medical Science》 SCIE CAS 2019年第4期582-588,共7页 当代医学科学(英文)
基金 This work was supported by grants from the National Natural Science Foundation of China (No.81570737, No.81370947, No.81570736, No.81770819, No.81500612, No.81400832, No.81600637, No.81600632, and No.81703294) the National Key Research and Development Program of China (No.2016YFC1304804 and No.2017YFC1309605) the Jiangsu Provincial Key Medical Discipline (No.ZDXKB2016012) the Key Project of Nanjing Clinical Medical Science the Key Research and Development Program of Jiangsu Province of China (No.BE2015604 and No.BE2016606) the Jiangsu Provincial Medical Talent (No.ZDRCA2016062) the Nanjing Science and Technology Development Project (No.201605019).
  • 相关文献

参考文献2

二级参考文献39

  • 1潘孝仁,中华内分泌代谢杂志,1994年,10卷,135页
  • 2潘孝仁,Diabetes Care,1993年,16卷,150页
  • 3胡英华,中华内科杂志,1993年,32卷,173页
  • 4团体著者,中华内科杂志,1981年,20卷,678页
  • 5潘孝仁,中华内科杂志,1995年,34卷,108页
  • 6F.R. Brunelli, T. Poggio, Face recognition: Features versus templates, IEEE Trans. Pattern Anal. Mach. Intell. 15 (10) (1993) 1042-1052.
  • 7D.W. Hanson, Q. Ji, In the eye of the beholder: A survey of models for eyes and gaze, IEEE Transaction on Pattern Analysis and Machine Intelligence 32 (2010) 478-500.
  • 8K.N. Kim, R.S. Ramakrishna, Vision-based eye-gaze tracking for human computer interface, in: Proc. IEEE Int'l Conf. Systems, Man, and Cybernetics, 1999, Vol. 2, pp. 324-329.
  • 9R. Kothari. J.L. Mitchell, Detection of eye locations in unconstrained visual images, in: Proc. lnt'l Conf. Image Processing, 1996, Vol. 3, pp. 519-522.
  • 10M. Nixon, Eye spacing measurement for facial recognition, in: Proc. SPIE Applications of Digital Image Processing, 1985, pp. 279-283.

共引文献424

同被引文献10

引证文献4

二级引证文献10

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部