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Cancer Imaging Phenomics via CaPTk: Multi-Institutional Prediction of Progression-Free Survival and Pattern of Recurrence in Glioblastoma.

JCO clinical cancer informatics | 2020

To construct a multi-institutional radiomic model that supports upfront prediction of progression-free survival (PFS) and recurrence pattern (RP) in patients diagnosed with glioblastoma multiforme (GBM) at the time of initial diagnosis.

Pubmed ID: 32191542 RIS Download

Research resources used in this publication

None found

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Associated grants

  • Agency: NINDS NIH HHS, United States
    Id: R01 NS042645
  • Agency: NIH HHS, United States
    Id: S10 OD023495
  • Agency: NIBIB NIH HHS, United States
    Id: T32 EB004311
  • Agency: NCI NIH HHS, United States
    Id: U24 CA189523

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Cancer Imaging Phenomics Toolkit (tool)

RRID:SCR_017323

Software platform for analysis of radiographic cancer images. Used as quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

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