Quantitative Physiologic MRI Combined with Feature Engineering for Developing Machine Learning-Based Prediction Models to Distinguish Glioblastomas from Single Brain Metastases

Quantitative Physiologic MRI Combined with Feature Engineering for Developing Machine Learning-Based Prediction Models to Distinguish Glioblastomas from Single Brain Metastases

<b>Background</b>: The accurate and early distinction of glioblastomas (GBMs) from single brain metastases (BMs) provides a window of opportunity for reframing treatment strategies enabling optimal and timely therapeutic interventions. We sought to leverage physiologically sensitive para...

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Bibliographic Details
Main Authors: Seyyed Ali Hosseini, Stijn Servaes, Brandon Hall, Sourav Bhaduri, Archith Rajan, Pedro Rosa-Neto, Steven Brem, Laurie A. Loevner, Suyash Mohan, Sanjeev Chawla
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Diagnostics
Subjects:
glioblastomas
brain metastases
MRI
machine learning
feature engineering
Online Access:https://www.mdpi.com/2075-4418/15/1/38

Internet

https://www.mdpi.com/2075-4418/15/1/38

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