个性化医疗
计算机科学
预测建模
机器学习
数据挖掘
人工智能
生物信息学
生物
作者
Silvia Oviedo,Josep Vehı́,Remei Calm,Joaquim Armengol
摘要
Abstract This paper presents a methodological review of models for predicting blood glucose (BG) concentration, risks and BG events. The surveyed models are classified into three categories, and they are presented in summary tables containing the most relevant data regarding the experimental setup for fitting and testing each model as well as the input signals and the performance metrics. Each category exhibits trends that are presented and discussed. This document aims to be a compact guide to determine the modeling options that are currently being exploited for personalized BG prediction.
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