関連する実験動画

Updated: Jun 15, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

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放射線報告におけるエンティティ分類と関係マッピングを強化する2段階の大型言語モデルアプローチ

Chaiho Shin1, Dareen Eom1, Sang Min Lee2

  • 1Interdisciplinary Program of Medical Informatics, College of Medicine, Seoul National University, Seoul, Republic of Korea.

Scientific reports
|August 27, 2025
PubMed
まとめ

この研究では,放射線報告の分析のために,トランスフォーマー (BERT) の二方向エンコーダー表現と大規模な言語モデル (LLM) を使用する2段階のパイプラインを導入します. この方法は,放射線学的発見を構造化することによって,医療画像のラベル付けの診断精度を高めます.

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