使用瑞典语和丹麦语的资源去识别挪威临床文本
Anastasios Lamproudis1, Sara Mora2, Therese Olsen Svenning1
1Norwegian Centre for E-health Research, Tromsø, Norway.
AMIA ... Annual Symposium proceedings. AMIA Symposium
|January 15, 2024
概括
本研究探讨使用瑞典数据来改善挪威临床文本中保护健康信息 (PHI) 的识别. 增加瑞典数据集与挪威实体显著提高了丹麦和挪威文本的非识别性能.
科学领域:
- 自然语言处理自然语言处理.
- 临床信息学 临床信息学
- 计算语言学 计算语言学
背景情况:
- 有限的注释数据集阻碍了自然语言处理 (NLP) 在挪威临床文本中识别受保护的健康信息 (PHI).
- 瑞典语是一个密切相关的语言,由于其可用的注释PHI数据,它提供了一个潜在的资源.
研究的目的:
- 调查利用瑞典注释数据用于挪威PHI识别的可行性.
- 评估文本增强技术对非识别性能的影响.
主要方法:
- 使用瑞典数据集注释PHI信息进行培训.
- 应用各种文字处理和增强技术,包括注入和生成挪威和斯堪的纳维亚命名实体.
- 评估了挪威和丹麦文本的非识别任务的模型性能,包括特定的挪威胃外科手术库.
主要成果:
- 文本增强策略,特别是注入和生成相关实体,明显改善了去识别性能.
- 在丹麦语和挪威语文文本中证实了增强的积极影响.
- 对挪威胃外科文本的模型性能评估验证了增强方法的有效性.
结论:
- 利用像瑞典语这样的密切相关语言的资源是克服挪威临床NLP数据短缺的可行策略.
- 文本增强技术显著提高了临床文本中受保护健康信息识别的准确性.
- 开发的方法显示了改善斯堪的纳维亚语言的脱标的前景.
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