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相关概念视频

Substance Use Disorders Affecting Sleep01:24

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Substance use disorders involve a pattern of using drugs more extensively than intended and continuing use despite harmful consequences. This includes legal substances like alcohol and nicotine, as well as illegal drugs. These disorders often involve both physical and psychological dependence, reflecting compulsive use of substances that significantly alter thoughts, feelings, and behaviors, contributing to a major public health issue.
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Drug Dependence01:17

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Medications are typically administered to achieve therapeutic effects. Some drugs can modify an individual's mood and perception, frequently resulting in various enjoyable experiences. However, this can result in drug dependency, a condition marked by continuous drug use despite potential negative consequences. Drug dependency primarily falls into two categories: psychological and physical dependence. Psychological dependence occurs when the pleasurable feelings induced by the drug...
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Diagnostic and Statistical Manual of Mental Disorders (DSM)01:27

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The Diagnostic and Statistical Manual of Mental Disorders (DSM) serves as the primary classification system for mental health disorders, providing standardized diagnostic criteria for clinicians and researchers. First published by the American Psychiatric Association (APA) in 1952, the DSM has undergone several revisions to reflect evolving psychiatric understanding. The fifth edition, DSM-5, released in 2013, introduced key updates that expanded diagnostic categories and modified diagnostic...
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During the development of a new pharmaceutical, the manufacturer initially assigns a code name to the drug. Once approved, the drug receives a United States Adopted Name (USAN)—a generic, nonproprietary designation. Upon being listed in the United States Pharmacopeia, this nonproprietary name becomes the drug's official name. Additionally, the manufacturer assigns a proprietary name or trademark, which serves as the brand name under which the drug is marketed. It is worth noting that...
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Drug Abuse and Addiction: Pharmacological Phenomena01:15

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Drug dependence, abuse, and addiction are complex phenomena that can precipitate various abnormal states. Physical dependence refers to a state of pharmacological adaptation to a drug. This adaptation often results in tolerance—a reduced response to the drug after repeated administrations. When the drug use is abruptly stopped, withdrawal symptoms occur due to the body's need to readjust from the pharmacologically induced imbalance. However, tolerance and withdrawal symptoms do not...
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Language and Cognition01:27

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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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从使用大型语言模型的临床笔记中解读物质使用障碍的严重程度.

Maria Mahbub1, Gregory M Dams2, Sudarshan Srinivasan3

  • 1Oak Ridge National Laboratory, Oak Ridge, TN, USA. mahbubm@ornl.gov.

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此摘要是机器生成的。

大型语言模型 (LLM) 可以有效地从临床笔记中提取物质使用障碍 (SUD) 的严重程度,优于传统方法. 这一进步有助于对SUD患者进行更好的风险评估和个性化治疗计划.

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科学领域:

  • 计算语言学计算语言学
  • 医疗信息学医学信息学
  • 精神病学是一个精神病学.

背景情况:

  • 药物使用障碍 (SUD) 对健康和社会产生重大影响,需要准确的识别和治疗.
  • 目前的诊断编码系统 (例如,ICD-10) 缺乏全面SUD评估所需的细节性.
  • 临床笔记包含重要的,细粒度的SUD信息,但对传统的自然语言处理 (NLP) 方法来说很难解析.

研究的目的:

  • 调查大语言模型 (LLM) 在从非结构化的临床笔记中提取SUD严重性信息的有效性.
  • 开发和评估基于LLM的工作流程,以提高SUD诊断的细节性.
  • 改善SUD患者的风险评估和治疗计划.

主要方法:

  • 开发了一个新的工作流程,利用零射击学习与精心设计的LLMs提示.
  • 开源的LLM,Flan-T5,被用来进行实验.
  • 根据基于规则的方法评估绩效,重点关注SUD诊断的11个类别.

主要成果:

  • 与基于规则的方法相比,LLM在提取SUD严重性信息方面表现出更好的回忆力.
  • 拟议的LLM工作流有效地解析了各种临床语言,克服了传统NLP的局限性.
  • 在11个不同的SUD诊断类别中成功提取了严重程度信息.

结论:

  • 从临床文本中准确地提取颗粒状SUD严重性数据,LLM显示出显著的希望.
  • 这种方法可以增强现有的诊断编码系统的局限性.
  • 这些发现支持使用LLM来改善SUD患者护理中的临床决策.