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#3229 The use of deep learning models to predict progression-free survival in patients with neuroendocrine tumors: Results from phase 3 of the RAISE project

Introduction: Response Evaluation Criteria in Solid Tumors (RECIST) assesses treatment response via tumor progression in patients with neuroendocrine tumors (NET). RAISE combined deep learning models (DLM) with sum of the longest diameter (SLD) of liver lesions and chromogranin A (CgA) to find a surrogate endpoint for RECIST to early predict progression-free survival (PFS).

Conference: 18th Annual ENETS Concerence (2021)

Presenting Author: Pavel M

Authors: Pavel M, Dromain C, Ronot M, Schaefer N, Mandair D,

Keywords: neuroendocrine tumor, deep learning models, progression-free survival, prediction,