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Social Foundations of Self II: The Generalized Other01:20

Social Foundations of Self II: The Generalized Other

246
According to George Herbert Mead, as children progress beyond the game stage, they develop a more comprehensive understanding of societal rules and norms. This cognitive and social development enables them to internalize the expectations of the broader community, refining their ability to regulate behavior.Consistent participation in organized activities is crucial in helping children recognize that their actions are not isolated but contribute to a more significant, interconnected group...
246
Physiological Foundation of Stress01:24

Physiological Foundation of Stress

648
Stress triggers a coordinated physiological response involving the sympathetic nervous system (SNS) and the hypothalamic-pituitary-adrenal (HPA) axis. This dual activation ensures that the body is prepared for both immediate and prolonged stress management. The process begins with the perception of a stressor. This initial phase activates the SNS, leading to the rapid release of adrenaline (epinephrine) from the adrenal glands.
Role of the Sympathetic Nervous System
Adrenaline triggers the...
648
Chronic Pancreatitis II: Collaborative Care01:29

Chronic Pancreatitis II: Collaborative Care

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The management of chronic pancreatitis is multifaceted, involving a comprehensive approach that includes thorough assessment, diagnostic testing, and a variety of management strategies.
Assessment:
353
Theoretical Foundations of Nursing Practice01:30

Theoretical Foundations of Nursing Practice

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Theories play an essential role in organizing patient care. Theories refer to a proposed or followed belief, policy, or procedure that is the basis for action. Nursing theories are knowledge-based concepts that guide nurses' actions, influence nursing education and practice, and allow nurses to care for their patients.
Theories provide a perspective to assess patients' conditions and organize data and methods. They also assist in analyzing and interpreting information. They represent a...
17.4K
Social Foundations of Self I: Play and Game01:24

Social Foundations of Self I: Play and Game

205
The development of self in children is deeply rooted in social interactions, mainly through stages of play and structured games. These stages, outlined by sociologist George Herbert Mead, illustrate how children progressively learn to understand and adopt social roles, forming a cohesive sense of self.The Play Stage: Imitation and Simple Role-TakingIn the early years of childhood, the play stage is characterized by imitative behavior, where children engage in role-playing based on familiar...
205
Social Foundations of Self III: Self-Evaluation01:30

Social Foundations of Self III: Self-Evaluation

190
Self-evaluation is the process by which individuals assess their abilities, behaviors, and characteristics based on feedback from others. Charles H. Cooley observed that a person’s self-perception is primarily influenced by how others see and judge them. He suggested that individuals form their identities based on their interpretations of others' reactions. As a result, social interactions play a crucial role in shaping self-esteem and personal identity. These external evaluations often...
190

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相关实验视频

Updated: Jan 29, 2026

Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis
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Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis

Published on: June 18, 2020

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一个基础模型驱动的多视图协作框架,用于半监督的3D医疗图像细分.

Lina Li1,2, Bin Wang2, Hong Zhang3

  • 1Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, China.

Frontiers in medicine
|January 28, 2026
PubMed
概括

本研究引入了一种新的半监督学习框架,用于3D医疗图像细分,利用基础模型和多视图协作来提高准确性,减少注释. 该方法提高了跨多种成像模式的细分性能.

关键词:
基础模型的基础模型.医疗图像细分 医疗图像细分多视图学习学习多视图学习细分任何东西模型模型.半监督学习 半监督学习

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相关实验视频

Last Updated: Jan 29, 2026

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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:

  • 3D医学图像细分对于临床决策至关重要,但需要大量的手动注释.
  • 半监督学习 (SSL) 通过使用有限的标记数据与丰富的未标记数据提供了一个解决方案.
  • 标注成本和时间限制阻碍了3D细分的广泛应用.

研究的目的:

  • 开发一个高效的半监督的3D医学图像细分框架.
  • 为了减少对高质量的voxel级注释的依赖.
  • 为了提高在不同医学成像模式的细分精度和通用性.

主要方法:

  • 提出了一个基于基础模型的多视角协作学习框架.
  • 利用了分段任何模型 (SAM) 类似的基础模型的零射击能力.
  • 使用协作融合模块集成的轴向,斜向和冠状视图.

主要成果:

  • 拟议的方法在MRI脑瘤和PET心脏细分任务上优于现有的基于SAM的半监督方法.
  • 证明了器官和瘤划分的边界精度提高.
  • 在不同的成像模式中展示了强大的可转移性.

结论:

  • 基础模型驱动的多视图协作学习范式推进了半监督的3D医疗图像细分.
  • 提供可扩展和临床相关的解决方案,减少注释负担.
  • 在各种医学成像模式中保持高分段精度.