A machine learning approach for predicting perihematomal edema expansion in patients with intracerebral hemorrhage

Objectives Preventing the expansion of perihematomal edema (PHE) represents a novel strategy for the improvement of neurological outcomes in intracerebral hemorrhage (ICH) patients. Our goal was to predict early and delayed PHE expansion using a machine learning approach. Methods We enrolled 550 pat...

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Veröffentlicht in:	European radiology 2023-06, Vol.33 (6), p.4052-4062
Hauptverfasser:	Chen, Yihao, Qin, Chenchen, Chang, Jianbo, Lyu, Yan, Zhang, Qinghua, Ye, Zeju, Li, Zhaojian, Tian, Fengxuan, Ma, Wenbin, Wei, Junji, Feng, Ming, Yao, Jianhua, Wang, Renzhi
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial Intelligence Brain Edema - diagnostic imaging Brain Edema - etiology Cerebral Hemorrhage - complications Cerebral Hemorrhage - diagnostic imaging Computed Tomography Diagnostic Radiology Edema Edema - complications Edema - diagnostic imaging Hematoma Hematoma - complications Hematoma - diagnostic imaging Hemorrhage Humans Imaging Indicators Internal Medicine Interventional Radiology Learning algorithms Machine Learning Medical diagnosis Medical imaging Medicine Medicine & Public Health Neuroradiology Performance prediction Radiology Radiomics Ultrasound
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