Using causality modeling and Fuzzy Lattice Reasoning algorithm for predicting blood glucose

作者：

Highlights：

• Predicting blood glucose level is always a multi-disciplines challenge.

• So far many researchers attempted prediction based on “batch” data that are accumulated over time.

• In this paper we used Fuzzy Lattice Reasoning in order to generate rules by processing continuous data stream.

• The rules that are generated by FLR contain min–max ranges for each influential factors that are fuzzy in nature.

• The rules will be useful in calibrating the insulin dosages and other therapical intervention.

摘要

•Predicting blood glucose level is always a multi-disciplines challenge.•So far many researchers attempted prediction based on “batch” data that are accumulated over time.•In this paper we used Fuzzy Lattice Reasoning in order to generate rules by processing continuous data stream.•The rules that are generated by FLR contain min–max ranges for each influential factors that are fuzzy in nature.•The rules will be useful in calibrating the insulin dosages and other therapical intervention.

论文关键词：Insulin-dependent diabetes mellitus,Diabetes therapy,Medical decision-support,Fuzzy Lattice Reasoning,Predictive Apriori

论文评审过程：Available online 17 July 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.07.035