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Updated: Feb 28, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Published on: December 6, 2024

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臨床面接におけるPTSD検出：自然言語処理手法と大規模言語モデルの比較分析

Feng Chen1, Dror Ben-Zeev2, Gillian Sparks3

  • 1Department of Biomedical Informatics and Health Education, University of Washington, Box 358047 Seattle, WA 98195, USA2Behavioral Research in Technology and Engineering (BRiTE) Center, Department of Psychiatry and Behavioral Sciences, University of Washington, 3751 W Stevens Wy NE Seattle, WA 98195, USA, fengc9@uw.edu.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|February 27, 2026
PubMed
まとめ

心的外傷後ストレス障害（PTSD）の自動検出における自然言語処理（NLP）は有望です。SentenceBERTのような埋め込みベースの手法が、臨床面接からのPTSD分類において最も高い精度を達成しました。

キーワード:
自然言語処理心的外傷後ストレス障害機械学習埋め込み大規模言語モデル

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