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関連する概念動画

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...
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Theoretical Foundations of Nursing Practice01:30

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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 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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関連する実験動画

Updated: Jan 28, 2026

A Novel Surgical Technique As a Foundation for In Vivo Partial Liver Engineering in Rat
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放射線科および画像診断における基盤モデル開発のための生成AI：工学的視点

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
まとめ

生成AIは、自己教師あり学習と合成データ生成を可能にすることにより、放射線科における医療基盤モデルを進歩させる上で極めて重要です。これらのAIモデルは、主要な課題に対処し、スケーラブルで適応性の高い医療AIインフラストラクチャへの道を開きます。

キーワード:
生成AI基盤モデル放射線科医療画像自己教師あり学習合成データマルチモーダル学習

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関連する実験動画

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科学分野:

  • 人工知能
  • 医用画像
  • 基盤モデル

背景:

  • 放射線科における注釈付きデータは限られており、異種です。
  • 生成AIは、自己教師あり学習と合成データ生成のソリューションを提供します。
  • 生成AIは、医療AIにおけるスケーラビリティ、マルチモーダルアライメント、データ多様性の課題に対処します。

研究 の 目的:

  • 医療基盤モデルにおける生成AIの役割をレビューすること。
  • 生成モデルフレームワークと表現学習技術を探求すること。
  • 臨床アプリケーションのためのマルチモーダル大規模言語モデル（MLLM）を説明すること。

主な方法:

  • 生成モデル（VAE、拡散、自己回帰フレームワーク）のレビュー。
  • ハイブリッド設計と表現学習（マスクオートエンコーディング、対照学習）の探求。
  • 視覚、テキスト、臨床データを統合するためのMLLMの設計とトレーニングの説明。

主要な成果:

  • 生成AIモデルは医療基盤モデルのバックボーンを形成します。
  • ハイブリッド設計と表現学習はモデルのパフォーマンスを向上させます。
  • MLLMは、レポート生成や臨床推論などのアプリケーションのために多様なデータを統合します。

結論:

  • 生成AIは、スケーラブルで適応性があり、プライバシーに配慮した医療AIを可能にします。
  • ケーススタディは、これらのモデルの実用的なアプリケーションを示しています。
  • 将来の方向性には、信頼性の高いAI展開のための幻覚、一般化、規制上の課題への対処が含まれます。