Automated data preparation for in vivo tumor characterization with machine learning

Automated data preparation for in vivo tumor characterization with machine learning

BackgroundThis study proposes machine learning-driven data preparation (MLDP) for optimal data preparation (DP) prior to building prediction models for cancer cohorts.MethodsA collection of well-established DP methods were incorporated for building the DP pipelines for various clinical cohorts prior...

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Bibliographic Details
Main Authors: Denis Krajnc, Clemens P. Spielvogel, Marko Grahovac, Boglarka Ecsedi, Sazan Rasul, Nina Poetsch, Tatjana Traub-Weidinger, Alexander R. Haug, Zsombor Ritter, Hussain Alizadeh, Marcus Hacker, Thomas Beyer, Laszlo Papp
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-10-01
Series:Frontiers in Oncology
Subjects:
cancer
hybrid imaging
PET
data preprocessing
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.1017911/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2022.1017911/full

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