相关实验视频

Updated: Jun 2, 2025

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

温度对利用大型语言模型从临床试验出版物中提取信息的影响

Paul Windisch^1,2, Fabio Dennstädt², Carole Koechli¹

¹Department of Radiation Oncology, Cantonal Hospital Winterthur, Winterthur, CHE.

|January 15, 2025

概括

大型语言模型 (LLM) 在温度设置高达1.50.的生物医学文本挖掘中显示出一致的性能. 较高的温度,特别是超过1.75,导致预测准确性降低,例如命名实体识别等任务.

科学领域:

生物医学信息学生物医学信息学
自然语言处理自然语言处理.

背景情况:

大型语言模型 (LLM) 越来越多地用于生物医学研究中的数据提取.
对于LLM参数 (如温度) 对生物医学文本挖掘的影响还不太清楚.
在安全的温度设置上缺乏共识,以便在这个领域提供可靠的LLM性能.

研究的目的:

为了评估不同温度设置对生物医学文本挖掘任务的LLM性能的影响.
评估临床试验出版物的命名实体识别和分类中的LLM准确性.
确定最佳和安全的温度范围,用于LLM应用在分析生物医学文本.

主要方法:

使用GPT-4o和GPT-4o-mini模型分析了临床试验出版物的两个数据集.
对于每个模型,测试了从0.00到2.00的9个温度设置.
模型执行了命名实体识别 (提取参与者数) 和分类 (识别RCT/瘤学重点).

主要成果:

无论是GPT-4o还是GPT-4o-mini都保持了超过98.7%的正确格式预测,温度高达1.50.0.
正确格式化预测的明显下降发生在1.75和2.00之间的温度.
关键性能指标在测试温度中保持稳定,主要是在更高设置时的预测格式化下降.

结论:

在1.50或以下的LLM温度设置确保生物医学文本挖掘任务的一致性性能.
更高的温度设置 (1.50以上) 可能导致性能降低,特别是在预测格式化中.
这些发现表明,控制温度范围对于可靠的NLP应用在分析生物医学文献中至关重要.

关键词:

大型语言模型.自然语言处理自然语言处理.温度的温度的温度的温度的温度文本采矿文本采矿是什么变压器的变压器是一个变压器.

更多相关视频

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

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

Published on: September 20, 2018

Author Spotlight: Computing the Effects of a Local Radiofrequency Hyperthermia Intervention on Tumor Biomechanics

Author Spotlight: Computing the Effects of a Local Radiofrequency Hyperthermia Intervention on Tumor Biomechanics

Published on: December 1, 2023

相关概念视频

Factors Affecting Body Temperature

Factors Affecting Body Temperature

As a nurse, it is vital to understand the factors affecting body temperature to monitor variations and effectively evaluate deviations from regular.
Factors may include:

Statistical Software for Data Analysis and Clinical Trials

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...

Improving Translational Accuracy

Improving Translational Accuracy

Regression Toward the Mean

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...