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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Publicado en:Neuro Oncol
Autores principales: 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
Lenguaje:Inglês
Publicado: Oxford University Press 2020
Materias:
Neuroimaging
Acceso en línea: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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