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相关概念视频

The Effect of Aging on Tissues01:19

The Effect of Aging on Tissues

2.0K
Several body functions deteriorate with age. The external signs of aging are easily identifiable. For example, the skin becomes dry, less elastic, and thins out, forming wrinkles. The skin of the face begins to appear looser due to a decrease in the levels of elastic and collagen fibers in the connective tissue. Additionally, melanin production in the hair follicle decreases with age, resulting in gray hair. Moreover, the senses of sight and hearing decline, so glasses and hearing aids may...
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Renewal of Skin Epidermal Stem Cells01:12

Renewal of Skin Epidermal Stem Cells

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The skin is divided into epidermis, dermis, and hypodermis, the skin's outermost, middle, and inner layers. The human epidermal layer regularly undergoes renewal, where old, dead cells are replaced by new cells. Epidermal stem cells or EpiSCs divide and differentiate to restore the lost cells. For the renewal process, some EpiSCs continuously self-renew. In contrast, few others differentiate into transit-amplifying cells, which later form prickle or spinous cells, followed by granular...
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Outcomes of maintenance BCG versus gemcitabine/docetaxel following BCG induction in NMIBC.

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Efficacy and outcomes of 360° laser retinopexy versus focal laser photocoagulation for retinal detachment.

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Associations of age-related macular degeneration and statin use: a cross-sectional analysis.

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Wearable-device geometry and tissue mechanical variability determine sacral soft-tissue loading and pressure injury risk.

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相关实验视频

Updated: May 16, 2025

Author Spotlight: Understanding Age-Related Macular Degeneration Pathophysiology with QAF Workflow
08:54

Author Spotlight: Understanding Age-Related Macular Degeneration Pathophysiology with QAF Workflow

Published on: May 26, 2023

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确定皮肤年龄的机器学习方法:系统审查

Eric McMullen1, Rokhshid Aflaki2, Pranav Jignesh Khatri2

  • 1Division of Dermatology, Department of Medicine, University of Toronto, Toronto, ON, Canada.

Journal of tissue viability
|April 2, 2025
PubMed
概括
此摘要是机器生成的。

机器学习使用面部图像和生物标志物准确估计皮肤衰老,但为了更好的概括性,需要不同的数据集. 本综述强调了年龄预测模型当前的准确性和局限性.

关键词:
人工智能的人工智能是人工智能.生物标志物生物标志物图像分析 图像分析机器学习是机器学习.皮肤老化 皮肤老化

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Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
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Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

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Author Spotlight: Enhancing Skin Model Diversity with Cost-Effective 3D Cellular Models
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Author Spotlight: Enhancing Skin Model Diversity with Cost-Effective 3D Cellular Models

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相关实验视频

Last Updated: May 16, 2025

Author Spotlight: Understanding Age-Related Macular Degeneration Pathophysiology with QAF Workflow
08:54

Author Spotlight: Understanding Age-Related Macular Degeneration Pathophysiology with QAF Workflow

Published on: May 26, 2023

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Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
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Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

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科学领域:

  • 皮肤病学 皮肤病学
  • 计算机科学 计算机科学
  • 生物技术是生物技术.

背景情况:

  • 皮肤衰老是一个复杂的过程,受内在和外在因素的影响.
  • 从皮肤外观准确地测定年龄是越来越多的研究领域.

研究的目的:

  • 在确定皮肤衰老方面系统地审查机器学习应用.
  • 评估当前文献的准确性,局限性和研究缺陷.

主要方法:

  • 在OVID Embase,OVID Medline,IEEE Xplore和ACM数字图书馆的系统文献搜索.
  • 选了1467篇文章,其中27篇被列入最终审查.
  • 分析机器学习模型性能和方法.

主要成果:

  • 机器学习模型实现了准确度,平均绝对误差在2.30至8.16年之间.
  • 全面图像分析是最常用的方法;生物标志物分析 (甲基组,蛋白质组) 也被使用.
  • 动态面部表情改善了年龄估计的准确性 (MAE 3.74);共聚焦显微镜显示高达85%的准确性.
  • 在许多研究中注意到存在偏差的高风险,这通常是由于样本大小小.

结论:

  • 机器学习显示了准确估计皮肤年龄的前景.
  • 未来的研究需要更多多样化的数据集 (种族,变量) 来提高概括性.
  • 解决像小样本大小这样的局限性对于稳健的模型开发至关重要.