Neoplastic and Non-neoplastic Acute Intracerebral Hemorrhage in CT Brain Scans: Machine Learning-Based Prediction Using Radiomic Image Features

Neoplastic and Non-neoplastic Acute Intracerebral Hemorrhage in CT Brain Scans: Machine Learning-Based Prediction Using Radiomic Image Features

Background: Early differentiation of neoplastic and non-neoplastic intracerebral hemorrhage (ICH) can be difficult in initial radiological evaluation, especially for extensive ICHs. The aim of this study was to evaluate the potential of a machine learning-based prediction of etiology for acute ICHs...

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Bibliographic Details
Main Authors: Jawed Nawabi, Helge Kniep, Reza Kabiri, Gabriel Broocks, Tobias D. Faizy, Christian Thaler, Gerhard Schön, Jens Fiehler, Uta Hanning
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-05-01
Series:Frontiers in Neurology
Subjects:
intracerebral hemorrhage
neoplastic hemorrhage
radiomics
machine learning
artificial intelligence
Online Access:https://www.frontiersin.org/article/10.3389/fneur.2020.00285/full

Internet

https://www.frontiersin.org/article/10.3389/fneur.2020.00285/full

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