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相关概念视频

Classification of Connective Tissues01:30

Classification of Connective Tissues

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The connective tissues have different properties and functions in the human body. They are broadly categorized into proper, supporting, or fluid connective tissues.
Connective Tissue Proper
Connective tissue proper is the most abundant class of connective tissues. As its name implies, it predominantly connects different tissues in the body. Depending on the cell types, ground substance, viscosity, and fiber types in the ECM, connective tissue proper is further categorized into loose and dense....
11.8K
Classification of Epithelial Tissues: Overview01:22

Classification of Epithelial Tissues: Overview

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Epithelial tissues are classified according to the shape of the cells and the number of cell layers formed. Cell shapes can be squamous (flattened and thin), cuboidal (square-like, as wide as it is tall), or columnar (rectangular, taller than it is wide). Additionally, the nucleus shape helps identify the type of epithelial cells. Squamous cells have flattened disc-shaped nuclei, cuboidal cells have spherical nuclei, and columnar cells have elongated nuclei.
Based on the number of cell layers,...
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Classification of Epithelial Tissues: Stratified Epithelium01:29

Classification of Epithelial Tissues: Stratified Epithelium

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Stratified epithelium consists of several stacked layers of cells. They provide the durability to withstand constant physical and chemical attacks. Stratified epithelium is named after the shape of the most apical layer of cells. Stratified squamous epithelium is the most common type found in the human body. In this tissue, the apical cells are squamous, whereas the basal layer contains either columnar or cuboidal cells. The basal cells divide to form new daughter cells, which gradually become...
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Force Classification01:22

Force Classification

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Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
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相关实验视频

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Deep Neural Networks for Image-Based Dietary Assessment
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压力和失禁相关皮肤炎的细粒度分类使用多模式深度学习:算法开发和验证研究.

Alexander Brehmer1, Constantin Seibold1, Jan Egger1,2,3

  • 1Institute for Artificial Intelligence in Medicine, Essen University Hospital, Girardetstr. 2, Essen, 45131, Germany, 0201 72377829.

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概括

一个新的深度学习框架准确地区分压力 (PU) 和失禁相关皮肤炎 (IAD),优于人类专家. 这种人工智能工具有助于临床医生诊断这些相似的伤口,以便更好地照顾患者.

关键词:
计算机视觉 计算机视觉深度学习是一种深度学习.图像的分类图像的分类.与失禁相关的皮肤炎多模式数据多模式数据压力的压力.合成图像的生成方法伤口分类 伤口分类

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相关实验视频

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科学领域:

  • 医疗保健中的人工智能
  • 医学图像分析 医学图像分析
  • 深度学习用于诊断.

背景情况:

  • 压力 (PUs) 和失禁相关皮肤炎 (IAD) 是常见的临床疾病,外表相似但治疗方法不同.
  • 准确区分PU和IAD对于有效的患者管理至关重要,但对医疗保健专业人员来说具有挑战性.

研究的目的:

  • 开发一个多式联网深度学习框架来分类PU和IAD.
  • 为了提高诊断准确度,使伤口严重性的细粒度分类成为可能.
  • 为临床医生提供决策支持工具,以区分PU和IAD.

主要方法:

  • 一组1555张伤口图像的数据集由伤口护理专家进行了注释.
  • 开发了一个多式联网深度学习框架,集成图像和患者数据.
  • 通过使用各种预处理,增强和训练技术,评估了四种模型 (CNN和变压器).

主要成果:

  • 在二元PU/IAD分类中,TinyViT变压器模型获得了93.23%的F1分数,超过了人类专家.
  • 在PU严重程度分类中,TinyViT表现出色 (75.43%的F1得分),而ConvNeXtV2在IAD分类中领先 (53.20%的F1得分).
  • 多式联网数据集成改善了二进制分类;整体准确度提高.

结论:

  • 多式联网深度学习框架准确地将PU与IAD区分开来,超过了人类专家的性能.
  • 这种人工智能工具可以减少诊断的不确定性,优化治疗,并改善患者的治疗结果.
  • 潜在的临床应用包括集成到EHR系统或移动诊断工具.