We proposed a personalized bolus advisor for patients with type 1 diabetes (T1D). A bolus advisor is a decision support system that recommends insulin doses based on an open-loop model-based optimization. To construct the bolus advisor, the optimal open-loop control of blood glucose (BG) concentration in T1D patients was represented as a multi-objective optimization problem. The insulin types, doses, and times for each injection were provided by the bolus advisor based on a personalized model and an average daily diet, which should be re-tuned frequently in specific time intervals. The constructed personalized model for T1D patients incorporates effects of the patient's age and body weight. Two treatment schemes using three types of insulin (regular, lispro, and NPH) were investigated. The proposed bolus advisor was tested in silico on three virtual patients with different ages (from 9 to 50 years old) and body weights (from 28 to 100 kg) considering ±40% under- and over-eating scenarios. The fluctuations in blood glucose and insulin levels are obviously wider in younger virtual subjects, which is showing the difficulties of the BG control problem in younger patients.

中文翻译：

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基于个性化模型和日常饮食的 1 型糖尿病多目标最佳胰岛素推注顾问

我们为 1 型糖尿病 (T1D) 患者提出了个性化的推注顾问。bolus advisor 是一种决策支持系统，它基于基于开环模型的优化推荐胰岛素剂量。为了构建推注顾问，T1D 患者血糖 (BG) 浓度的最佳开环控制被表示为多目标优化问题。每次注射的胰岛素类型、剂量和时间由推注顾问根据个性化模型和平均每日饮食提供，应在特定时间间隔内频繁重新调整。为 T1D 患者构建的个性化模型结合了患者年龄和体重的影响。研究了使用三种类型胰岛素（常规、赖脯和 NPH）的两种治疗方案。考虑到±40%的饮食不足和过度饮食的情况，提议的bolus advisor在三个不同年龄（从9岁到50岁）和体重（从28到100公斤）的虚拟患者身上进行了计算机模拟测试。较年轻的虚拟受试者血糖和胰岛素水平的波动明显更广泛，这表明年轻患者的血糖控制问题存在困难。