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相关概念视频

Physiological Foundation of Stress01:24

Physiological Foundation of Stress

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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...
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Social Foundations of Self II: The Generalized Other01:20

Social Foundations of Self II: The Generalized Other

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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
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...
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Radiological Investigation I: X-ray and CT01:30

Radiological Investigation I: X-ray and CT

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Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and...
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Social Foundations of Self I: Play and Game01:24

Social Foundations of Self I: Play and Game

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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...
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Social Foundations of Self III: Self-Evaluation01:30

Social Foundations of Self III: Self-Evaluation

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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...
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相关实验视频

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A Novel Surgical Technique As a Foundation for In Vivo Partial Liver Engineering in Rat
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用于开发放射学和成像学基础模型的生成人工智能:工程视角

June-Goo Lee1, Sunggu Kyung1, Namkug Kim1

  • 1Department of Convergence Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.

Biomedical engineering letters
|January 26, 2026
PubMed
概括

生成性人工智能对于推进放射学医学基础模型至关重要,因为它能够实现自我监督学习和合成数据生成. 这些人工智能模型解决了关键挑战,为可扩展和适应的医疗人工智能基础设施铺平了道路.

科学领域:

  • 人工智能的人工智能是人工智能.
  • 医学成像医学成像
  • 基金会模型 基金会模型

背景情况:

  • 放射学上的注释数据有限且异质.
  • 生成型人工智能为自我监督学习和合成数据生成提供解决方案.
  • 生成型人工智能解决了医疗人工智能的可扩展性,多模式对齐和数据多样性挑战.

研究的目的:

  • 审查生成AI在医学基础模型中的作用.
  • 探索生成模型框架和表示学习技术.
  • 描述用于临床应用的多式联通大型语言模型 (MLLMs).

主要方法:

  • 对生成模型 (VAE,扩散,自动回归框架) 的审查.
  • 探索混合设计和表示学习 (掩盖自动编码,对比学习).
  • 描述MLLM设计和培训,以整合视觉,文本和临床数据.

主要成果:

  • 生成型人工智能模型构成了医疗基础模型的骨干.
  • 混合设计和表示学习提高模型性能.
  • 多种类型的LLM集成了各种数据,用于诸如报告生成和临床推理等应用.

结论:

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  • 生成型人工智能使得医疗人工智能具有可扩展性,适应性和隐私意识.
  • 案例研究证明了这些模型的实际应用.
  • 未来的方向包括解决幻觉,概括和可靠的AI部署的监管挑战.