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相关概念视频

Diabetes Mellitus: Overview and Type I Subtype01:22

Diabetes Mellitus: Overview and Type I Subtype

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Diabetes mellitus is a chronic metabolic disorder characterized by high blood glucose levels due to inadequate insulin production, insulin resistance, or both. The condition affects millions worldwide and can significantly impact their health and quality of life.
Type 1 diabetes is an autoimmune disease in which the immune system mistakenly attacks and destroys the insulin-producing beta cells in the pancreas. As a result, the body is unable to produce sufficient insulin, and individuals with...
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Diabetes Mellitus: Type 2 and Gestational01:22

Diabetes Mellitus: Type 2 and Gestational

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Type 2 diabetes, characterized by insulin resistance, arises when the insulin receptors on cells lose responsiveness to insulin, diminishing the cell's capacity to take up glucose, resulting in elevated blood glucose levels. To receive a diagnosis of Type 2 diabetes, a series of blood glucose tests are necessary to assess whether the blood glucose falls within normal parameters. If the result is out of the normal range, a patient may be diagnosed as prediabetic or diabetic, depending on the...
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Pathophysiology of Diabetes01:20

Pathophysiology of Diabetes

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Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycemia. The four categories of diabetes are type 1 diabetes, type 2 diabetes, other specific types of diabetes, and gestational diabetes.
Type 1 diabetes is characterized by autoimmune-mediated destruction of pancreatic β cells, with environmental factors potentially triggering this process in genetically susceptible individuals. Despite many not having a family history, certain genes increase susceptibility,...
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Diabetes: Symptoms, Diagnosis, and Complications01:15

Diabetes: Symptoms, Diagnosis, and Complications

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For most patients, experiencing several weeks of polyuria, polydipsia, fatigue, and significant weight loss may indicate the presence of diabetes. Furthermore, adults displaying the phenotypic appearance of type 2 diabetes (particularly those who are obese and not initially insulin-requiring), may have islet cell autoantibodies, suggesting autoimmune-mediated β cell destruction and a diagnosis of latent autoimmune diabetes of adults (LADA). The categorization of glucose homeostasis is...
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Insulin: Biosynthesis, Chemistry, and Preparation01:25

Insulin: Biosynthesis, Chemistry, and Preparation

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The endoplasmic reticulum (ER) of pancreatic β-cells synthesizes preproinsulin, which consists of a signal peptide, A and B chains, and a C-peptide. Preproinsulin is then cleaved and folded into proinsulin, which translocates to the Golgi apparatus for sorting and packaging into secretory granules. In these granules, enzymatic clipping generates insulin and C-peptide.
Damage or functional impairment of β-cells inhibits insulin production, leading to diabetes. Diabetes treatment...
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Carbohydrate Metabolism01:36

Carbohydrate Metabolism

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Carbohydrates are polymers composed of molecules containing atoms of carbon, hydrogen and oxygen. One gram of carbohydrate can provide four kilo-calories of energy, which makes it the most efficient instant energy source.
Starch accounts for approximately 60% of the carbohydrates consumed by humans. Since amylase enzymes cannot function in the stomach's acidic environment, starch can only be digested in the mouth and small intestine. Simple sugars are found naturally in milk and fruits in...
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相关实验视频

Updated: Jun 13, 2025

An In Ovo Model for Testing Insulin-mimetic Compounds
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一个可解释的人工智能软件系统用于预测糖尿病.

Parvathaneni Naga Srinivasu1,2, Shakeel Ahmed3, Mahmoud Hassaballah4,5

  • 1Department of Teleinformatics Engineering, Federal University of Ceará, Fortaleza, 60455-970, Brazil.

Heliyon
|September 10, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一个可解释的人工智能 (XAI) 系统,用于非侵入性糖尿病监测. 该新系统使用Bi-LSTM和CNN模型准确识别异常葡萄糖水平,改善患者的舒适性和监测.

关键词:
这是一个双LSTM.血糖水平在血液中的葡萄糖水平.卷积神经网络是一种卷积神经网络.超参数超参数是指超参数.在ROC曲线上,ROC曲线频谱图像的图像 频谱图像的图像

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相关实验视频

Last Updated: Jun 13, 2025

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科学领域:

  • 生物医学工程 生物医学工程
  • 医疗保健中的人工智能
  • 糖尿病 技术 技术

背景情况:

  • 最少侵入性的血糖监测会引起不适.
  • 有效的糖尿病监测对于管理医疗费用至关重要.
  • 现有的方法需要提取血液,这给持续监测带来了挑战.

研究的目的:

  • 开发一种可解释的人工智能 (XAI) 系统,用于进行非侵入性血糖水平分析.
  • 创建一个可理解的机器学习模型来预测和解释葡萄糖水平的结果.
  • 通过一个舒适而准确的监测系统来改善糖尿病监测.

主要方法:

  • 使用双向长短期记忆 (Bi-LSTM) 和卷积神经网络 (CNN) 进行异常葡萄糖水平分析.
  • 通过放置在身体上的葡萄糖氧化酶 (GOD) 条带获取葡萄糖水平数据.
  • 将信号数据转换为光谱图像以进行分类 (低,平均,异常葡萄糖).
  • 使用标记的光谱图像和XAI驱动的架构训练了一个个性化的监控模型.

主要成果:

  • 拟议的XAI模型有效地跟踪实时葡萄糖水平.
  • 使用混矩阵指标的性能评估显示出高准确度.
  • 该模型成功识别了高血糖水平的个体.

结论:

  • 开发的XAI系统为糖尿病监测提供了一个有前途的非侵入性方法.
  • 整合Bi-LSTM,CNN和XAI提高了葡萄糖监测的可理解性和准确性.
  • 这项技术有可能显著改善糖尿病的管理,并降低医疗保健成本.