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Multivariate Cox proportional hazards analysis results of clinical parameters.

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posted on 2019-10-02, 17:27 authored by Georgios Kaissis, Sebastian Ziegelmayer, Fabian Lohöfer, Katja Steiger, Hana Algül, Alexander Muckenhuber, Hsi-Yu Yen, Ernst Rummeny, Helmut Friess, Roland Schmid, Wilko Weichert, Jens T. Siveke, Rickmer Braren

Multivariate Cox proportional hazards analysis results of clinical parameters.

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A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy

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ROC-AUC pancreatic ductal adenocarcinoma HR patient survival diffusion-weighted-imaging-derived radiomic features KRT 81. Tumors PDAC FOLFIRINOX chemotherapy Purpose Development vs 1606 radiomic features KRT 81- patients gradient-boosted survival regression model response Radiomic feature importance KRT 81- tumor subtypes

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