为MULTI-SITA项目和一般医学意大利自然语言数据定义一个预处理管道
Alice Cappello1, Sara Mora2, Daniele Roberto Giacobbe1,3
1Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
Studies in health technology and informatics
|October 23, 2023
概括
本研究引入了一种新的自然语言处理 (NLP) 预处理管道,用于意大利医学文本. 该工具提高了分析患者与医生对话的效率,以获得更好的医疗保健应用.
科学领域:
- 医疗信息学 医疗信息学
- 计算语言学 计算语言学
背景情况:
- 自然语言处理 (NLP) 已经改变了医疗保健,特别是通过聊天机器人的远程医疗援助.
- 有效的NLP应用取决于可靠的数据预处理,而意大利医疗文本的进展落后.
研究的目的:
- 开发和验证意大利医疗数据的预处理管道.
- 为了解决意大利NLP技术医学术语的具体挑战.
主要方法:
- 开发了一个基于Python的预处理管道.
- 使用了诸如Enchant和NLTK之类的库.
- 雇员拥抱脸的BERT和BART模型用于高级处理.
主要成果:
- 该管道在真实患者与医生的对话中成功测试.
- 证明了对各种医疗数据类型的适应性.
- 开发的算法是一个灵活的结构.
结论:
- 创建的管道为意大利医疗NLP提供了重大进展.
- 这项工作支持以意大利语开发更复杂的AI驱动的医疗保健解决方案.
- 灵活的设计允许在各种医疗数据环境中广泛应用.
关键词:
巴特·巴特 (BART BART) 是一个著名的艺术家.贝尔特 (BERT) 公司聊天机器人 聊天机器人意大利语 意大利语 意大利语多个位置 (Multi-SITA)机器学习 机器学习医疗数据 医疗数据自然语言处理自然语言处理.更多相关视频
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