Cancer imaging phenomics toolkit: Quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome

Christos Davatzikos, Saima Rathore, Spyridon Bakas, Sarthak Pati, Mark Bergman, Ratheesh Kalarot, Patmaa Sridharan, Aimilia Gastounioti, Nariman Jahani, Eric Cohen, Hamed Akbari, Birkan Tunc, Jimit Doshi, Drew Parker, Michael Hsieh, Aristeidis Sotiras, Hongming Li, Yangming Ou, Robert K. Doot, Michel BilelloYong Fan, Russell T. Shinohara, Paul Yushkevich, Ragini Verma, Despina Kontos

Roy and Diana Vagelos Division of Biology & Biomedical Sciences (DBBS)
Institute for Informatics, Data Science and Biostatistics (I2DB)
Institute of Clinical and Translational Sciences (ICTS)
Computational Imaging Research Center
Siteman Cancer Center
DBBS - Biomedical Informatics and Data Science
DBBS - Neurosciences

Research output: Contribution to journal › Article › peer-review

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Cancer imaging phenomics toolkit: Quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome

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