NIMG-66. AI-BASED PROGNOSTIC IMAGING BIOMARKERS FOR PRECISION NEUROONCOLOGY AND THE RESPOND CONSORTIUM

AI-based methods have shown great promise in a variety of biomedical research fields, including neurooncologic imaging. For example, machine learning methods have offered informative predictions of overall survival (OS) and progression-free survival (PFS), differentiation between pseudoprogression (...

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Detalhes bibliográficos
Publicado no:Neuro Oncol
Main Authors: Davatzikos, Christos, Badve, Chaitra, Kazerooni, Anahita Fathi, Bashyam, Vishnu, Bakas, Spyridon, Colen, Rivka, Mahajan, Abhishek, Balaña, Carmen, Capellades, Jaume, Puig, Josep, Jain, Rajan, Sloan, Andrew E, Marcus, Daniel S, Choi, Yoon Seong, Lee, Seung-Koo, Chang, Jong Hee, Poisson, Laila M, Griffith, Brent, Dicker, Adam P, Flanders, Adam E, Booth, Thomas C, Rathore, Saima, Akbari, Hamed, Sako, Chiharu, Bilello, Michel, Shukla, Gaurav, Brem, Steven, Lustig, Robert, Mohan, Suyash, Nasrallah, MacLean, O’Rourke, Donald M, Bagley, Stephen, Barnholtz-Sloan, Jill S
Formato: Artigo
Idioma:Inglês
Publicado em: Oxford University Press 2020
Assuntos:
Neuroimaging
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7651203/
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/neuonc/noaa215.679
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