Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Diabetes Mellitus: Type 2 and Gestational01:22

Diabetes Mellitus: Type 2 and Gestational

4.3K
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...
4.3K
Diabetes Mellitus: Overview and Type I Subtype01:22

Diabetes Mellitus: Overview and Type I Subtype

4.8K
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...
4.8K
Diabetes: Symptoms, Diagnosis, and Complications01:15

Diabetes: Symptoms, Diagnosis, and Complications

2.0K
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...
2.0K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Gallstone disease classification using SLOA-optimized CatBoost classifier with explainable AI.

PloS one·2026
Same author

Multi-Objective AI Optimization of Plastic Waste Pyrolysis Integrating Energy Return on Investment for Circular Polymer Recycling.

Polymers·2026
Same author

Quad-Element Implantable MIMO Antenna for Wireless Capsule Endoscopy.

Sensors (Basel, Switzerland)·2026
Same author

Feature reduction using swarm optimization and random forest classifiers for early diabetes risk prediction.

Scientific reports·2026
Same author

A wideband slot antenna for RF energy harvesting.

Scientific reports·2026
Same author

A Systematic Review of Multimodal Frameworks for Assessing Health Vulnerability in Academicians Across Ergonomic, Lifestyle, and Dietary Domains.

Healthcare (Basel, Switzerland)·2026
Same journal

Correction: Luca et al. Global and Regional Diagnostic Results of Progress Toward Cervical Cancer Elimination, According to the WHO Strategy: A Systematic Literature Review with Narrative Synthesis. <i>Diagnostics</i> 2026, <i>16</i>, 1224.

Diagnostics (Basel, Switzerland)·2026
Same journal

Association Between Systemic Inflammatory Response Biomarkers and Disease Activity in Systemic Lupus Erythematosus: A Multi-Center Retrospective Study.

Diagnostics (Basel, Switzerland)·2026
Same journal

Vertebrogenic Low Back Pain and Basivertebral Nerve Ablation: A Review of Mechanisms, Imaging-Driven Selection, and Clinical Outcomes.

Diagnostics (Basel, Switzerland)·2026
Same journal

Multivalvular Carcinoid Heart Disease: The Role of Echocardiography in Diagnosis and Selection for Heterotopic Bicaval Valve Implantation.

Diagnostics (Basel, Switzerland)·2026
Same journal

Data-Efficient and Explainable Multimodal Survival Prediction in NSCLC Using Deep Image Embeddings, Clinical Variables, and Gradient-Boosted Trees.

Diagnostics (Basel, Switzerland)·2026
Same journal

Anomalous Left Coronary Artery from the Pulmonary Artery: Cinematic Volume Rendering Technique for Enhanced Anatomic Visualization.

Diagnostics (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Jan 13, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.9K

使用特征选择算法和基于增强的机器学习分类器预测糖尿病.

Fatima Rahman1, Sheyum Hossain1, Jun-Jiat Tiang2

  • 1Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, Bangladesh.

Diagnostics (Basel, Switzerland)
|October 29, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种机器学习框架,用于准确预测糖尿病,通过优化的特征选择改进早期检测,并对不平衡的数据集增强算法.

关键词:
增强了分类器算法.糖尿病预测 糖尿病预测特性选择算法 (FSAs) 是一种机器学习是机器学习.医学诊断 医学诊断 医学诊断

更多相关视频

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

7.4K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.9K

相关实验视频

Last Updated: Jan 13, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.9K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

7.4K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.9K

科学领域:

  • 医疗信息学 医疗信息学
  • 计算生物学 计算生物学
  • 医疗保健中的机器学习

背景情况:

  • 糖尿病是一种主要的全球健康问题,需要及早诊断以预防并发症.
  • 精确的糖尿病预测受到有限,杂和不平衡的数据集的阻碍.
  • 现有的方法在特征选择,类不平衡和数据预处理方面面临挑战.

研究的目的:

  • 为增强糖尿病预测开发一种新的机器学习框架.
  • 为了应对特征选择,类不平衡和数据预处理的挑战.
  • 提高早期糖尿病检测模型的准确性和可解释性.

主要方法:

  • 对五种特征选择算法的系统评估:递归特征消除,灰狼优化器,粒子优化器,遗传算法和Boruta.
  • 利用交叉验证和SHAP分析来进行特征选择和可解释性.
  • 使用LightGBM (LGBM) 和XGBoost (XGBoost) 分类算法.

主要成果:

  • 博鲁塔特征选择算法确定了前五个特征,通过LightGBM分类器实现了卓越的性能.
  • 获得了85.16%的准确性和85.41%的F1分数.
  • 与其他配置相比,训练时间减少了54.96%.

结论:

  • 拟议的框架为早期发现糖尿病提供了强大而准确的解决方案.
  • 在Pima印度糖尿病数据集和DiaHealth数据集上验证的有效性.
  • 为早期发现糖尿病提供了一种具有成本效益,可解释性和临床相关性的方法.