Case-base maintenance of a personalised and adaptive CBR bolus insulin recommender system for type 1 diabetes

作者：

Highlights：

• Case-base maintenance of a CBR bolus recommender system.

• Personalised and adaptive attributes weight learning of the CBR recommender.

• System tested with UVA/PADOVA diabetes simulator with positive results.

摘要

•Case-base maintenance of a CBR bolus recommender system.•Personalised and adaptive attributes weight learning of the CBR recommender.•System tested with UVA/PADOVA diabetes simulator with positive results.

论文关键词：Case-based reasoning,Insulin recommender system,Case-base maintenance,Attribute weight learning,Patient empowerment,Diabetes

论文评审过程：Received 10 September 2018, Revised 13 November 2018, Accepted 19 December 2018, Available online 20 December 2018, Version of Record 26 December 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.12.036