Automatic classification of glycaemia measurements to enhance data interpretation in an expert system for gestational diabetes
作者：
Highlights：
• Highly accurate classifier to associate glycemia with main meals.
• Design based on the evaluation of machine learning and feature selection strategies.
• Application in a telemedicine and decision support system in a clinical environment.
• Minimal patient intervention. (1.22% of glycemia measurements reclassified).
• Enhance quality of decision support and recommendations provided in telemedicine.
摘要
•Highly accurate classifier to associate glycemia with main meals.•Design based on the evaluation of machine learning and feature selection strategies.•Application in a telemedicine and decision support system in a clinical environment.•Minimal patient intervention. (1.22% of glycemia measurements reclassified).•Enhance quality of decision support and recommendations provided in telemedicine.
论文关键词：Automatic classification,Decision support,Expert systems,Gestational diabetes,Machine learning,Telemedicine
论文评审过程：Received 23 July 2015, Revised 11 July 2016, Available online 14 July 2016, Version of Record 21 July 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.07.019
