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Updated: Jan 8, 2026

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
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TSHに基づく先天性甲状腺機能低下症スクリーニングの機械学習とリサンプリングアルゴリズムを用いた強化

Alexander De Furia1,2, Paula Branco3, Matthew Henderson4,5

  • 1School of Electrical Engineering and Computer Science, University of Ottawa, 800 King Edward Ave., Ottawa, Ontario, K1N 5N6, Canada. adefu020@uottawa.ca.

BMC medical informatics and decision making
|December 23, 2025
PubMed
まとめ

機械学習は、感度を100%維持しながら陽性的中率を60%向上させることで、先天性甲状腺機能低下症スクリーニングを大幅に改善します。この高度なアプローチは、新生児の偽陽性を減らし、不要な診断コストを削減します。

キーワード:
クラス不均衡先天性甲状腺機能低下症機械学習新生児スクリーニング希少疾患希少イベント検出

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Low blood levels of the thyroid hormones — triiodothyronine (T3) and thyroxine (T4) — signal the hypothalamus to release the thyrotropin-releasing hormone (TRH). TRH then reaches the pituitary gland and stimulates the release of thyroid-stimulating hormone(TSH) into the bloodstream.
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