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Language Development

Language Development

Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...

Improving Translational Accuracy

Improving Translational Accuracy

Improving Translational Accuracy

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

Language and Cognition

Language and Cognition

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.

Components of Language

Components of Language

Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.

Higher Mental Functions of the Brain: Language

Higher Mental Functions of the Brain: Language

Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...

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相关实验视频

Updated: Jan 17, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

使用大型语言模型从临床笔记中提取语言信息.

Lingfei Qian¹, Na Hong¹, Yujia Zhou¹

¹Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA.

International journal of medical informatics

|September 24, 2025

概括

此摘要是机器生成的。

大型语言模型 (LLM) 可以准确地从临床笔记中提取患者的语言能力,改善医疗保健公平. 这个命名实体识别 (NER) 管道增强了通信和资源分配.

关键词:

跨站点验证跨站点验证大型语言模型.命名实体认可命名实体认可患者语言信息患者语言信息

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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

相关实验视频

Last Updated: Jan 17, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

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Published on: September 20, 2018

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

科学领域:

自然语言处理自然语言处理.
临床信息学临床信息学
医疗保健服务研究医疗服务研究

背景情况:

患者的语言能力对于公平的护理和研究至关重要.
电子健康记录 (EHR) 的语言数据往往不完整或不准确.
异构的文档化做法阻碍了多机构的数据使用.

研究的目的:

使用大型语言模型 (LLM) 开发和评估命名实体识别 (NER) 管道.
准确地从非结构化的临床笔记中提取详细的患者语言状态.
为研究和实践提供可扩展和通用化的语言信息提取.

主要方法:

定义了四个语言状态类别:流利使用,部分能力,缺乏理解和不相关的提及.
来自耶鲁纽黑文医院 (YNHH) 和MIMIC-III的注释数据集.
评估专有 (GPT-4o) 和开源 (LLaMA3,BERT) LLM 在零射击和微调设置中.
评估跨站点通用性. 评估跨站点通用性.

主要成果:

在没有微调的情况下,GPT-4o获得了高F1分数 (87%YNHH,82%MIMIC).
微调的开源模型 (BERT,LLaMA3) 显示了同等或更高的性能.
与传统模型相比,LLM,特别是LLaMA3的跨机构通用性更强.
不相关的语言提及是最具挑战性的类别.

结论:

该NER框架准确地从临床叙述中提取细微的语言信息.
高准确度和通用性支持大规模的,以语言为重点的研究.
影响包括改善患者提供者沟通,口译服务和公平的医疗保健.