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Quantitative Physiologic MRI Combined with Feature Engineering for Developing Machine Learning Based Prediction Models in Distinguishing Glioblastomas from Single Brain Metastases

2024-10-14

Abstract excerpt

<title>Abstract</title> <p>Background Accurate and early distinction of glioblastomas (GBMs) from single brain metastases (BMs) provide a window of opportunity for reframing treatment strategies enabling optimal and timely therapeutic interventions. We sought to leverage physiologically sensitive parameters derived from diffusion tensor imaging (DTI), and dynamic susceptibility contrast (DSC)-perfusion weighted...

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Literature Corpus work
5faf1b07-9d8a-54ae-836f-25d289322ab4
DOI
10.21203/rs.3.rs-4883888/v1
Open publication

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Quantitative Physiologic MRI Combined with Feature Engineering for Developing Machine Learning Based Prediction Models in Distinguishing Glioblastomas from Single Brain MetastasesDOI 10.21203/rs.3.rs-4883888/v1
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