Multimodal nomogram integrating deep learning radiomics and hemodynamic parameters for early prediction of post-craniotomy intracranial hypertension

Multimodal nomogram integrating deep learning radiomics and hemodynamic parameters for early prediction of post-craniotomy intracranial hypertension

Abstract To evaluate the effectiveness of deep learning radiomics nomogram in distinguishing early intracranial hypertension (IH) following primary decompressive craniectomy (DC) in patients with severe traumatic brain injury (TBI) and to demonstrate its potential clinical value as a noninvasive too...

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Bibliographic Details
Main Authors: Zunfeng Fu, Jing Wang, Wenyi Shen, Yanqing Wu, Jiajun Zhang, Yan Liu, Chongqiang Wang, Yanlin Shen, Ye Zhu, Weifu Zhang, Chunju Lv, Lin Peng
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Severe traumatic brain injury
Intracranial pressure
Ultrasound radiomics
Machine learning
Optic nerve sheath diameter(ONSD)
Transcranial color doppler (TCCD)
Online Access:https://doi.org/10.1038/s41598-025-09115-7
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