Radiomics-based machine learning model for predicting secondary decompressive craniectomy in TBI patients after emergent craniotomy with bone flap replacement

Abstract Background Secondary decompressive craniectomy (DC) is commonly integrated into tiered therapeutic protocols in the intensive care unit (ICU) to manage elevated intracranial pressure following traumatic brain injury (TBI). Identifying high-risk patients in advance could enable early interve...

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Autors principals:	Tiange Chen, Ganzhi Liu, Ziyuan Liu, Jiacheng Liu, Jinfang Liu, Zhongyi Sun
Format:	Artigo
Idioma:	Inglês
Publicat:	BMC 2026-01-01
Col·lecció:	Chinese Neurosurgical Journal
Matèries:	Radiomics Traumatic brain injury Decompressive craniectomy Machine learning
Accés en línia:	https://doi.org/10.1186/s41016-025-00423-5
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