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Updated: May 3, 2026

A Volumetric Method for Quantification of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage
08:12

A Volumetric Method for Quantification of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage

Published on: July 28, 2018

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透明な機械学習により,サブアラクノイド出血と血管縮の診断用グリカンバイオマーカーが検出される

Attila Garami1, Máté Czabajszki2, Béla Viskolcz3

  • 1Institute of Energy, Ceramic and Polymer Technology, University of Miskolc, 3515 Miskolc, Hungary.

International journal of molecular sciences
|August 28, 2025
PubMed
まとめ

血清のN-グリコミックデータを用いた解釈可能な決定樹モデルは,健康な個体,サバクラノイド出血 (SAH) 患者,および脳血管縮 (CVS) 患者とを区別することができる. このアプローチは,SAHとCVSの早期診断とリスク分層化に役立ちます.

キーワード:
N-グリカン脳血管の意思決定ツリー解釈可能な機械学習液体染色学マススペクトロメトリー血清の糖化サバラクノイド出血

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