Machine Learning Models for 3-Month Outcome Prediction Using Radiomics of Intracerebral Hemorrhage and Perihematomal Edema from Admission Head Computed Tomography (CT)

Machine Learning Models for 3-Month Outcome Prediction Using Radiomics of Intracerebral Hemorrhage and Perihematomal Edema from Admission Head Computed Tomography (CT)

<b>Background</b>: Intracerebral hemorrhages (ICH) and perihematomal edema (PHE) are respective imaging markers of primary and secondary brain injury in hemorrhagic stroke. In this study, we explored the potential added value of PHE radiomic features for prognostication in ICH patients....

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Bibliographic Details
Main Authors: Fiona Dierksen, Jakob K. Sommer, Anh T. Tran, Huang Lin, Stefan P. Haider, Ilko L. Maier, Sanjay Aneja, Pina C. Sanelli, Ajay Malhotra, Adnan I. Qureshi, Jan Claassen, Soojin Park, Santosh B. Murthy, Guido J. Falcone, Kevin N. Sheth, Seyedmehdi Payabvash
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Diagnostics
Subjects:
intracerebral hemorrhage
perihematomal edema
radiomics
machine learning
Online Access:https://www.mdpi.com/2075-4418/14/24/2827
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