生物医学自然语言处理中的2023年:致敬大型语言模型和生成AI
Cyril Grouin1, Natalia Grabar2
1Université Paris Saclay, CNRS, LISN, 91400 Orsay, France.
Yearbook of medical informatics
|April 8, 2025
概括
2023年顶级的生物医学自然语言处理 (NLP) 论文专注于用于数据增强和域调整的语言模型. 这些进展对于改善医疗保健中的人工智能和分析各种数据源至关重要.
科学领域:
- 生物医学自然语言处理 (NLP)
- 医疗保健中的人工智能
背景情况:
- 生物医学自然语言处理 (NLP) 的领域正在迅速发展.
- 识别具有高影响力的出版物对于跟踪进展至关重要.
研究的目的:
- 从2023年开始,确定和分析生物医学NLP中最好的科学出版物.
- 突出当前的趋势和该领域的关键研究领域.
主要方法:
- 系统地搜索Medline和ACL的诗集数据库.
- 自动评分和手动列出候选人论文的入围名单.
- 评审过程,包括外部审稿人的评价和编辑的选择.
主要成果:
- 在2,148个出版物中,选出了两个顶级论文.
- 选择的论文重点是用于数据增强,域调整和蒸的语言模型.
- 应用包括使用深度学习的社交媒体内容和电子健康记录.
结论:
- 2023年的趋势包括经典的NLP任务,医学教育,聊天机器人和生成AI.
- 具体解决的问题是癌症,COVID-19 (包括后期条件) 和心理健康.
- 语言模型的进步有助于处理非英语语言和语言可移植性.
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