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 pati...

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Bibliografski detalji
Izdano u:PLoS One
Glavni autori: Kaissis, Georgios, Ziegelmayer, Sebastian, Lohöfer, Fabian, Steiger, Katja, Algül, Hana, Muckenhuber, Alexander, Yen, Hsi-Yu, Rummeny, Ernst, Friess, Helmut, Schmid, Roland, Weichert, Wilko, Siveke, Jens T., Braren, Rickmer
Format: Artigo
Jezik:Inglês
Izdano: Public Library of Science 2019
Teme:
Research Article
Online pristup:https://ncbi.nlm.nih.gov/pmc/articles/PMC6774515/
https://ncbi.nlm.nih.gov/pubmed/31577805
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0218642
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