Predicción de transformación hemorrágica post-trombectomía mediante DSA cuantitativa habilitada por aprendizaje

Hui Li1, Chao Pang1, Xiaoying Guo1

  • 1Department of Neurosurgery, the first hospital of Hebei Medical University, Hebei Medical University, Shijiazhuang, China.

Scientific reports
|January 22, 2026
PubMed
Resumen

Este estudio desarrolló un modelo de aprendizaje automático utilizando datos cuantitativos de DSA (qDSA) y datos clínicos para predecir la transformación hemorrágica (TH) después de la trombectomía mecánica (TM) para el accidente cerebrovascular isquémico agudo. El modelo logró un AUC de 0,86, lo que ayuda a predecir mejor los resultados de los pacientes.

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