Ability of 18F-FDG Positron Emission Tomography Radiomics and Machine Learning in Predicting KRAS Mutation Status in Therapy-Naive Lung Adenocarcinoma

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Document type:: Zeitschriftenaufsatz
Author(s):: Zhang, Ruiyun ; Shi, Kuangyu ; Hohenforst-Schmidt, Wolfgang ; Steppert, Claus ; Sziklavari, Zsolt ; Schmidkonz, Christian ; Atzinger, Armin ; Hartmann, Arndt ; Vieth, Michael ; Förster, Stefan
Title:: Ability of 18F-FDG Positron Emission Tomography Radiomics and Machine Learning in Predicting KRAS Mutation Status in Therapy-Naive Lung Adenocarcinoma
Keywords:: Article ; PET ; KRAS ; machine learning ; lung adenocarcinoma ; radiomic features
Journal title:: Cancers
Year:: 2023
Journal volume:: 15
Journal issue:: 14
Fulltext / DOI:: doi:10.3390/cancers15143684
Publisher:: MDPI
E-ISSN:: 2072-6694
Date of publication:: 19.07.2023
CC license:: by, https://creativecommons.org/licenses/by/4.0

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