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相关概念视频

Social Anxiety Disorder01:28

Social Anxiety Disorder

34
Social anxiety disorder, also known as social phobia, is characterized by an intense fear of social situations where one might face humiliation, rejection, embarrassment, or negative evaluation. This disorder leads individuals to avoid activities like casual conversations, public speaking, or seemingly simple tasks such as eating, signing documents, or swimming, in public settings. Its impact extends beyond discomfort, often significantly interfering with daily functioning and quality of life.
34
Autism Spectrum Disorder01:19

Autism Spectrum Disorder

89
Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by persistent deficits in social communication and interaction alongside restrictive and repetitive behaviors or interests. ASD is sometimes accompanied by intellectual impairment.
These core symptoms manifest differently among individuals, ranging from mild to severe. The disorder's complexity extends beyond its clinical presentation, encompassing a diverse range of biological, cognitive, and sociocultural influences.
89
Modeling in Therapy01:26

Modeling in Therapy

72
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
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Stereotype Content Model02:16

Stereotype Content Model

14.7K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.7K
Generalized Anxiety Disorder01:30

Generalized Anxiety Disorder

133
Generalized Anxiety Disorder (GAD) is a chronic condition characterized by excessive and uncontrollable worry that persists for at least six months, significantly interfering with daily functioning. Unlike situational anxiety, which arises in response to specific stressors, GAD often occurs without a clear cause. Individuals may experience disproportionate worry about work, health, or relationships. For instance, a person might continuously fear poor health despite normal medical evaluations or...
133
Behavior Therapy01:22

Behavior Therapy

48
Behavior therapy incorporates diverse techniques rooted in classical conditioning principles to address maladaptive behaviors and anxiety disorders. These methods aim to reduce avoidance behaviors, foster adaptive coping mechanisms, and alter associations between stimuli and responses, making them effective in a wide range of therapeutic contexts.
Exposure therapy is a cornerstone of behavioral treatment for anxiety disorders. It involves systematic exposure to feared stimuli, either in real...
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Updated: Jun 30, 2025

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome
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萨德克萨伊:使用多种可解释的人工智能技术预测社会焦虑障碍

Krishnaraj Chadaga1, Srikanth Prabhu1, Niranjana Sampathila2

  • 1Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka 576104, India.

SLAS technology
|March 20, 2024
PubMed
概括
此摘要是机器生成的。

社会焦虑障碍 (SAD) 可以通过分析患者症状的机器学习模型来诊断. AdaBoost和后勤回归实现了88%的准确性,识别了早期检测的关键诊断因素.

关键词:
人工智能的人工智能是人工智能.临床决策支持系统在DSM-5中,可解释的人工智能机器学习 机器学习社会焦虑障碍 (SAD) 是一种社会焦虑障碍.

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相关实验视频

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科学领域:

  • 精神病学和计算机科学
  • 人工智能在心理健康诊断中的应用

背景情况:

  • 社会焦虑障碍 (SAD) 或社会恐惧症,涉及对负面判断的持续恐惧,影响社会和职业生活.
  • 抑郁症是由环境和生物因素的复杂相互作用引起的.
  • 诊断依赖于精神健康障碍诊断和统计手册 (DSM-5) 中概述的标准,考虑身体,情绪和人口统计症状.

研究的目的:

  • 研究机器学习 (ML) 技术在诊断社会焦虑障碍 (SAD) 的有效性.
  • 开发一种可解释的SAD诊断框架,使用可解释的人工智能 (XAI).

主要方法:

  • 利用人口,情绪和身体症状数据进行SAD诊断.
  • 应用了多个机器学习分类器,包括AdaBoost和后勤回归.
  • 采用四种可解释的人工智能 (XAI) 技术来解释模型预测.

主要成果:

  • AdaBoost和后勤回归模型实现了最高的诊断准确率,达到88%.
  • XAI的分析确定了"利博维茨社会焦虑量表问卷"和"公开演讲的恐惧"作为关键的诊断属性.
  • 该研究建立了一个临床决策支持系统框架,用于SAD识别.

结论:

  • 机器学习模型在诊断社会焦虑障碍方面表现出很高的准确性.
  • XAI提高了基于ML的SAD诊断的解释性,突出了关键的贡献因素.
  • 开发的框架在教育,医疗保健和职业环境中对早期SAD检测有潜在的应用.