Predicting Mechanical Thrombectomy Outcome and Time Limit through ADC Value Analysis: A Comprehensive Clinical and Simulation Study Using Machine Learning

Predicting Mechanical Thrombectomy Outcome and Time Limit through ADC Value Analysis: A Comprehensive Clinical and Simulation Study Using Machine Learning

Predicting outcomes after mechanical thrombectomy (MT) remains challenging for patients with acute ischemic stroke (AIS). This study aimed to explore the usefulness of machine learning (ML) methods using detailed apparent diffusion coefficient (ADC) analysis to predict patient outcomes and simulate...

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Bibliographic Details
Main Authors: Daisuke Oura, Soichiro Takamiya, Riku Ihara, Yoshimasa Niiya, Hiroyuki Sugimori
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Diagnostics
Subjects:
acute ischemic stroke
MRI
ADC
machine learning
Online Access:https://www.mdpi.com/2075-4418/13/13/2138

Internet

https://www.mdpi.com/2075-4418/13/13/2138

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