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

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

PURPOSE:Development of a supervised machine-learning model capable of predicting clinically relevant molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) from diffusion-weighted-imaging-derived radiomic features. METHODS:The retrospective observational study assessed 55 surgical PDAC patien...

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Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0218642

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https://doi.org/10.1371/journal.pone.0218642

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