更正：探索一种使用BERT在患者叙事领域中提取多位乳腺癌患者关注点的方法，并通过使用掩码语言模型的领域适应对其进行优化。
Correction: Exploring a method for extracting concerns of multiple breast cancer patients in the domain of patient narratives using BERT and its optimization by domain adaptation using masked language modeling.
作者信息
Watabe Satoshi, Watanabe Tomomi, Yada Shuntaro, Aramaki Eiji, Yajima Hiroshi, Kizaki Hayato, Hori Satoko
出版信息
PLoS One. 2025 Aug 1;20(8):e0329664. doi: 10.1371/journal.pone.0329664. eCollection 2025.
Abstract
[This corrects the article DOI: 10.1371/journal.pone.0305496.].
摘要
[本文更正了文章的数字对象标识符：10.1371/journal.pone.0305496。]
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Correction: Exploring a method for extracting concerns of multiple breast cancer patients in the domain of patient narratives using BERT and its optimization by domain adaptation using masked language modeling.更正：探索一种使用BERT在患者叙事领域中提取多位乳腺癌患者关注点的方法，并通过使用掩码语言模型的领域适应对其进行优化。
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本文引用的文献
1
Exploring a method for extracting concerns of multiple breast cancer patients in the domain of patient narratives using BERT and its optimization by domain adaptation using masked language modeling.使用 BERT 及其通过屏蔽语言建模进行领域自适应优化来提取患者叙述中多个乳腺癌患者关注点的方法研究。
PLoS One. 2024 Sep 6;19(9):e0305496. doi: 10.1371/journal.pone.0305496. eCollection 2024.
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