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Updated: Jan 20, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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肝細胞癌における深層学習由来のCT特徴量を用いた血管侵襲予測のハイブリッド画像臨床モデル

Shidi Miao1, Mingxuan Wang1, Qi Dong1

  • 1School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, China.

Physical and engineering sciences in medicine
|January 19, 2026
PubMed
まとめ

脂肪組織は、肝臓がん（HCC）患者における微小血管侵襲（MVI）を予測するのに役立つ可能性がある。深層学習とCTスキャンを用いた新しいハイブリッドモデルは、MVI診断の精度を向上させ、放射線科医を上回る性能を示した。

キーワード:
深層学習小網膜MVIマルチモーダル全生存期間

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