2型糖尿病患者膳食摄入与胰岛素给药优化进化算法数据表1

该PDF数据集包含使用进化算法优化2型糖尿病患者膳食和胰岛素给药的补充研究数据,用于血糖控制优化。

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DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes

基本信息

模态
文本
大小
0.001806089 GB
许可
CC BY 4.0
创建/更新时间
2026-10-08
版本
v1

资源简介

2型糖尿病患者膳食摄入与胰岛素给药优化进化算法数据表1

【一句话概览】

本数据集是 figshare 公开的文本数据集,收录 1 个文件、合计 1.81 MB,主题涵盖 diabetes type 2 (T2D)、evolutionary algorithm (EA)、computational modeling、AI in diabetes、glyceamia regulation,可用于医学自然语言处理(实体识别、信息抽取等),CC BY 4.0 许可开放获取。

【数据集背景】

本数据集源站标题为《DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes.PDF》。配套论文《Insulin Pump Therapy for Patients With Type 2 Diabetes Mellitus: Evidence, Current Barriers, and New Technologies》发表于 Journal of Diabetes Science and Technology(2020),DOI:10.1177/1932296820928100。源站首次发布:2023-04-06。

【数据内容】

源站原始描述:The optimal management of type 2 diabetes (T2DM) is complex and involves an appropriate combination of diet, exercise, and different pharmacological treatments. Artificial intelligence-based tools have been shown to be very useful for the diagnosis and treatment of diverse pathologies, including diabetes. In the present study, we present a proof of concept of the potential of an evolutionary algorithm to optimize the meal size, timing and insulin dose for the control of glycemia. We found that a…

中文译文(机器翻译,仅供快速理解,请以原文为准):2型糖尿病(T2DM)的最佳管理很复杂,需要适当结合饮食、运动以及不同的药物治疗。基于人工智能的工具已被证明对包括糖尿病在内的多种疾病的诊断和治疗非常有用。在本研究中,我们展示了一项概念验证,证明进化算法在优化进餐量、进餐时间和胰岛素剂量以控制血糖方面具有潜力。我们发现,在一天中适当分配食物摄入量,可以减少将血糖维持在美国糖尿病协会(ADA)推荐范围内所需的胰岛素剂量,该范围适用于不同严重程度的T2DM患者。此外,我们还评估了对进食时间和进食量进行限制的影响,并发现随着饮食摄入受到的限制越多,控制血糖所需的胰岛素量就越大。在不久的将来,使用这些计算工具应能使T2DM患者根据其糖尿病的严重程度,优化个人的进餐计划和胰岛素剂量。

【数据结构与技术规格】

文件数 1 个,合计 1.81 MB。DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes.PDF:application/pdf,1.81 MB。数据集 DOI:10.3389/fphys.2023.1149698.s001。

【主题与分类】

源站学科分类:Animal Physiology - Biophysics、Animal Physiology - Cell、Animal Physiology - Systems、Comparative Physiology、Physiology not elsewhere classified、Reproduction。主题标签:diabetes type 2 (T2D)、evolutionary algorithm (EA)、computational modeling、AI in diabetes、glyceamia regulation。

【适用方向】

文本类数据可用于医学自然语言处理,如命名实体识别、信息抽取与文本分类。

【获取与许可】

源站页面:https://frontiersin.figshare.com/articles/dataset/DataSheet1_Evolutionary_algorithm_for_the_optimization_of_meal_intake_and_insulin_administration_in_patients_with_type_2_diabetes_PDF/22565518

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Gonzalez-Flo, Eva; Kheirabadi, Elaheh; Rodriguez-Caso, Carlos; Macía, Javier (2023). DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes.PDF. Frontiers. Dataset

【使用注意】

· 源站最后修改于 2023-06-21,引用时请注意版本时效。

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下载信息

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使用方式

数据集获取(Figshare)

命令行下载

curl -L -o "DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes.PDF" "https://ndownloader.figshare.com/files/40042015"

文件清单

  • DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes.PDF(1.81 MB)

文件总体积 1.81 MB(源站 API 实测)。

数据说明

The optimal management of type 2 diabetes (T2DM) is complex and involves an appropriate combination of diet, exercise, and different pharmacological treatments. Artificial intelligence-based tools have been shown to be very useful for the diagnosis and treatment of diverse pathologies, including diabetes. In the present study, we present a proof of concept of the potential of an evolutionary algorithm to optimize the meal size, timing and insulin dose for the control of glycemia. We found that an appropriate distribution of food intake throughout the day permits a reduction in the insulin dose required to maintain glycemia within the range recommended by the American Diabetes Association for patients with T2DM of a range of severities. Furthermore, the effects of restrictions to both the timing and amount of food ingested were assessed, and we found that an increase in the amount of insulin was required to control glycemia as dietary intake became more restricted. In the near future, the use of these computational tools should permit patients with T2DM to optimize their personal meal schedule and insulin dose, according to the severity of their diabetes.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fphys.2023.1149698.s001(source: https://frontiersin.figshare.com/articles/dataset/DataSheet1_Evolutionary_algorithm_for_the_optimization_of_meal_intake_and_insulin_administration_in_patients_with_type_2_diabetes_PDF/22565518)。

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