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

Diabetic Foot Ulcer01:31

Diabetic Foot Ulcer

Definition A diabetic foot ulcer (DFU) is a chronic, non-healing wound that develops in individuals with diabetes. It typically occurs on pressure-bearing areas such as the heel, metatarsal heads, or hallux, and carries a high risk of infection and amputation.Pathophysiology • The development of DFUs can be explained by four interconnected mechanisms: neuropathy, ischemia, infection, and impaired wound healing. • Neuropathy is the most common factor. Sensory neuropathy reduces pain perception,...

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

Joint spectro-temporal and perceptual feature learning using a dual-track attention network for music genre classification.

Frontiers in artificial intelligence·2026
Same author

CoNutriNet: a dual-branch architecture with DenseNet and graph-enhanced attention network for coffee nutrient deficiency classification.

Frontiers in plant science·2026
Same author

Classification of coffee leaf nutrient deficiencies using hybrid feature aggregation with hierarchical localized attention and MobileNet.

Frontiers in artificial intelligence·2026
Same author

A quantum-classical dual-track deep learning network for explainable Parkinson's disease classification.

Frontiers in artificial intelligence·2026
Same author

Development of Mobile Software "SRCardioCare" Prototype for Implementing Home-Based Exercise Program Among Patients After Adult Cardiac Surgical Revascularization: Qualitative Feasibility Study.

JMIR rehabilitation and assistive technologies·2026
Same author

Comparative nutritional and antioxidant profiling of Assam honeys: unveiling the untapped bioactivity of stingless bee honey.

Frontiers in nutrition·2026

相关实验视频

Updated: Jul 6, 2026

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.7K

一个可解释的深度学习模型用于糖尿病足的分类,使用swin变压器和高效的多尺度注意力驱动网络.

R Karthik1, Armaano Ajay2, Anshika Jhalani3

  • 1Centre for Cyber Physical Systems, Vellore Institute of Technology, Chennai, India.

Scientific reports
|February 3, 2025
PubMed
概括

结合Swin变压器和EMADN网络的新型深度学习模型准确地分类糖尿病足 (DFU). 这种双轨道方法改善了诊断,可能减少截肢和医疗保健成本.

关键词:
在美国,CNN是CNN.深度学习是一种深度学习.糖尿病足部 糖尿病足部混杂注意力 混杂注意力斯温变压器是什么意思

更多相关视频

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

455
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

359

相关实验视频

Last Updated: Jul 6, 2026

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.7K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

455
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

359

科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 计算机视觉 计算机视觉

背景情况:

  • 糖尿病足 (DFU) 是一种严重的糖尿病并发症,导致下肢截肢和严重的医疗负担.
  • 手动的DFU诊断是具有挑战性的,因为不同的视觉特征,往往导致错过诊断.

研究的目的:

  • 开发一个自动化,高效的深度学习模型,用于准确的糖尿病足的分类.
  • 引入一种新的双轨功能融合架构,以增强DFU检测.

主要方法:

  • 一种新的双轨模型,集成Swin变压器用于远程依赖和高效多尺度注意力驱动网络 (EMADN) 用于局部特征.
  • 两条轨道的特征地图都被连接在一起,并使用混合注意力来改进.
  • 基于Grad-CAM的可解释的人工智能 (XAI) 用于模型解释性.

主要成果:

  • 拟议的模型在DFUC-2021数据集上实现了78.79%的准确性和80%的宏观F1得分.
  • 超越现有的方法和预训练的卷积神经网络 (CNN) 架构.
  • 通过双轨架构证明了有效的特征提取和改进.

结论:

  • 新的双轨深度学习模型为自动和准确的糖尿病足分类提供了一个有希望的解决方案.
  • 这种方法有可能改善早期诊断,促进及时治疗,并减少糖尿病患者下肢截肢的发生率.