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 (PLOS ONE (2024) 19:9 (e0305496) DOI: 10.1371/journal.pone.0305496)

Satoshi Watabe; Tomomi Watanabe; Shuntaro Yada; Eiji Aramaki; Hiroshi Yajima; Hayato Kizaki; Satoko Hori

doi:10.1371/journal.pone.0329664

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 (PLOS ONE (2024) 19:9 (e0305496) DOI: 10.1371/journal.pone.0305496)

Satoshi Watabe
, Tomomi Watanabe
, Shuntaro Yada
, Eiji Aramaki
, Hiroshi Yajima
, Hayato Kizaki
, Satoko Hori

薬学科

研究成果: Comment/debate › 査読

抄録

The phrase “concerns of multiple” is incorrect in the article title. The correct title is: Exploring a method for extracting multiple concerns of breast cancer patients in the domain of patient narratives using BERT and its optimization by domain adaptation using masked language modeling. The correct citation is: Watabe S, Watanabe T, Yada S, Aramaki E, Yajima H, Kizaki H, et al. (2024) Exploring a method for extracting multiple concerns of breast cancer patients in the domain of patient narratives using BERT and its optimization by domain adaptation using masked language modeling. PLoS ONE 19 (9): e0305496. https://doi.org/10.1371/journal.pone.0305496.

本文言語	English
論文番号	e0329664
ジャーナル	PloS one
巻	20
号	8 August
DOI	https://doi.org/10.1371/journal.pone.0329664
出版ステータス	Published - 2025 8月

UN SDG

この成果は、次の持続可能な開発目標に貢献しています

SDG 3 すべての人に健康と福祉を

ASJC Scopus subject areas

一般

文献へのアクセス

10.1371/journal.pone.0329664

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フィンガープリント

「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 (PLOS ONE (2024) 19:9 (e0305496) DOI: 10.1371/journal.pone.0305496)」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル

Watabe, S., Watanabe, T., Yada, S., Aramaki, E., Yajima, H., Kizaki, H., & Hori, S. (2025). 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 (PLOS ONE (2024) 19:9 (e0305496) DOI: 10.1371/journal.pone.0305496). PloS one, 20(8 August), 記事 e0329664. https://doi.org/10.1371/journal.pone.0329664

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 (PLOS ONE (2024) 19:9 (e0305496) DOI: 10.1371/journal.pone.0305496). / Watabe, Satoshi; Watanabe, Tomomi; Yada, Shuntaro その他.
In: PloS one, Vol. 20, No. 8 August, e0329664, 08.2025.

研究成果: Comment/debate › 査読

Watabe, S, Watanabe, T, Yada, S, Aramaki, E, Yajima, H, Kizaki, H & Hori, S 2025, '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 (PLOS ONE (2024) 19:9 (e0305496) DOI: 10.1371/journal.pone.0305496)', PloS one, vol. 20, no. 8 August, e0329664. https://doi.org/10.1371/journal.pone.0329664

Watabe S, Watanabe T, Yada S, Aramaki E, Yajima H, Kizaki H その他. 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 (PLOS ONE (2024) 19:9 (e0305496) DOI: 10.1371/journal.pone.0305496). PloS one. 2025 8月;20(8 August):e0329664. doi: 10.1371/journal.pone.0329664

Watabe, Satoshi ; Watanabe, Tomomi ; Yada, Shuntaro その他. / 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 (PLOS ONE (2024) 19:9 (e0305496) DOI: 10.1371/journal.pone.0305496). In: PloS one. 2025 ; Vol. 20, No. 8 August.

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