Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques

MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures...

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Veröffentlicht in:Neuro-oncology (Charlottesville, Va.) Va.), 2016-03, Vol.18 (3), p.417-425
Hauptverfasser: Macyszyn, Luke, Akbari, Hamed, Pisapia, Jared M, Da, Xiao, Attiah, Mark, Pigrish, Vadim, Bi, Yingtao, Pal, Sharmistha, Davuluri, Ramana V, Roccograndi, Laura, Dahmane, Nadia, Martinez-Lage, Maria, Biros, George, Wolf, Ronald L, Bilello, Michel, O'Rourke, Donald M, Davatzikos, Christos
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Sprache:eng
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