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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

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Updated: Jun 14, 2025

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

一个大语言模型框架从PubMed案例报告中提取相对时间表.

Jing Wang¹, Jeremy C Weiss¹

¹National Library of Medicine, Bethesda, Maryland, USA.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science

|June 12, 2025

概括

本研究引入了一种系统,可以从报告中提取临床事件时间表,使用大型语言模型 (LLM). LLM显示高时间一致性,使得更好的患者轨迹分析.

科学领域:

医疗信息学医疗信息学
自然语言处理自然语言处理.
临床数据分析临床数据分析

背景情况:

准确的患者轨迹分析需要精确的临床事件时间.
电子健康记录往往缺乏详细的时间事件数据.
临床报告是无结构的,缺乏局部事件时间.

研究的目的:

开发一个系统,将临床病例报告转化为结构化的文字时间序列.
评估大型语言模型 (LLM) 在提取时间事件数据方面的性能.
使用PubMed开放访问 (PMOA) 库建立时间分析的基准.

主要方法:

开发了一个系统,从案例报告中创建文本事件时间对.
将PMOA案例报告上的手册注释与基于LLM的注释进行比较.
评估了LLM之间的时间事件提取协议.

主要成果:

在LLM模型中,事件回忆度适度 (0.80).
在LLM模型中,已识别的事件之间实现了高时间一致性 (0.95).
建立了用于时间分析的任务,注释和评估系统.

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Last Updated: Jun 14, 2025

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

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Published on: September 20, 2018

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Published on: December 6, 2024

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

结论:

从临床报告中,LLM可以有效地提取时间结构化的事件数据.
开发的系统和研究结果为医学时间分析提供了基准.
使用LLM利用PMOA语料库可以增强患者轨迹分析.