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相关概念视频

Higher Mental Functions of the Brain: Language01:10

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...
Typical Model Studies01:30

Typical Model Studies

Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
Language01:16

Language

Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
Components of Language01:24

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. “eh”). Phonemes combine to...
Language Development01:22

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...
Language and Cognition01:27

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.

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相关实验视频

Updated: Jul 1, 2026

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
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放射学大型语言模型兴起的趋势和轨迹:范围审查

Adhari Al Zaabi1, Rashid Alshibli2, Abdullah AlAmri2

  • 1Human and Clinical Anatomy Department, College of Medicine and Health Sciences, Sultan Qaboos University, P.O. Box 35, Al Khodh, Muscat, 123, Oman.

JMIR medical informatics
|December 9, 2025
PubMed
概括

大型语言模型 (LLM) 在放射学中显示出对报告生成和工作流优化等任务的承诺. 然而,它们的诊断准确性不一致,在广泛采用之前需要进一步的临床验证.

关键词:
在这里,我们可以看到AIAIAI.在 GPT-4 中使用.人工智能的人工智能是人工智能.临床决策支持 临床决策支持大型语言模型.自然语言处理自然语言处理.放射学 放射学是指放射学报告的生成 报告的生成范围审查 范围审查审查工作流的优化工作流的优化.

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科学领域:

  • 人工智能在医学中的应用
  • 医学成像信息学 医疗成像信息学
  • 放射学人工智能应用程序

背景情况:

  • 大型语言模型 (LLM) 正在迅速发展,在放射学领域的应用越来越多,包括报告生成,决策支持和工作流程优化.
  • 尽管它们具有潜力,但目前缺乏对LLM应用,性能和放射学领域的局限性进行全面评估.

研究的目的:

  • 系统地绘制目前LLMs在放射学中的应用.
  • 评估LLM在关键放射学任务中的表现.
  • 确定放射学LLM的局限性和未来研究方向.

主要方法:

  • 根据Arksey和O'Malley框架和PRISMA-ScR指南进行了范围审查.
  • 在PubMed,ScopusCOPUS和IEEE Xplore搜索了2022年1月至2024年12月的同行评审研究.
  • 包括放射学LLM的经验评估;不包括没有评估的评论和技术建议.

主要成果:

  • 包括67项研究,其中GPT-4是最常见的LLM (42%).
  • 主要使用案例包括决策支持 (58%),报告生成/总结 (24%) 和工作流程优化 (18%).
  • 在结构化文本任务中,LLM表现出色 (>94%准确度),但由于数据集偏差和有限的验证,其诊断性能变化 (16%-86%). 大多数研究都是单一中心的概念验证 (79.1%).

结论:

  • LLM 具有显著的潜力,可以增强放射学工作流程,特别是结构化报告和总结.
  • 目前的诊断性能不一致,需要强大的外部验证才能进行临床整合.
  • 未来的研究应侧重于对安全临床使用的域调整和多模式LLM的前性,多中心验证.