相关实验视频

Updated: Jun 23, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

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

Published on: December 6, 2024

在瘤学中用于健康信息提取的大型语言模型应用:范围审查

David Chen1, Saif Addeen Alnassar2, Kate Elizabeth Avison2

  • 1Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.

JMIR cancer
|March 28, 2025
PubMed
概括

大型语言模型 (LLM) 自动化瘤学中的临床数据提取,减少手工工作量. 快速工程和微调方面的进步显示出未来研究和临床整合的前景.

关键词:
在这里,我们可以看到AIAIAI.在法学士 (LLM) 课程中.在NLP中,我们使用了NLP.人工智能的人工智能是人工智能.聊天机器人 聊天机器人交谈代理人是一个对话代理人.数据提取数据提取.数字健康数字健康电子健康记录 电子健康记录卫生信息 卫生信息医疗技术 医疗技术 医疗技术大型语言模型自然语言处理自然语言处理.瘤学 在瘤学方面.范围审查 范围审查审查

更多相关视频

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems05:47

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

Published on: June 13, 2025

Constructing and Visualizing Models using Mime-based Machine-learning Framework06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

相关概念视频

Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...