Texture analysis

Open Access
A Machine Learning Approach Using PET/CT-based Radiomics for Prediction of PD-L1 Expression in Non-small Cell Lung Cancer
CHAE HONG LIM, YOUNG WHA KOH, SEUNG HYUP HYUN and SU JIN LEE

Anticancer Research December 2022, 42 (12) 5875-5884; DOI: https://doi.org/10.21873/anticanres.16096
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Prediction of Tumor Grade and Nodal Status in Oropharyngeal and Oral Cavity Squamous-cell Carcinoma Using a Radiomic Approach
VALERIA ROMEO, RENATO CUOCOLO, CARLO RICCIARDI, LORENZO UGGA, SIRIO COCOZZA, FRANCESCO VERDE, ARNALDO STANZIONE, VIRGINIA NAPOLITANO, DANIELA RUSSO, GIOVANNI IMPROTA, ANDREA ELEFANTE, STEFANIA STAIBANO and ARTURO BRUNETTI

Anticancer Research January 2020, 40 (1) 271-280; DOI: https://doi.org/10.21873/anticanres.13949
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CT Texture Analysis of Ductal Adenocarcinoma Downstaged After Chemotherapy
VALENTINA CIARAVINO, NICOLÒ CARDOBI, RICCARDO DE ROBERTIS, PAOLA CAPELLI, DAVIDE MELISI, FRANCESCA SIMIONATO, GIOVANNI MARCHEGIANI, ROBERTO SALVIA and MIRKO D'ONOFRIO

Anticancer Research August 2018, 38 (8) 4889-4895; DOI: https://doi.org/10.21873/anticanres.12803
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Associations Between PET Textural Features and GLUT1 Expression, and the Prognostic Significance of Textural Features in Lung Adenocarcinoma
YOUNG WHA KOH, SEONG YONG PARK, SEUNG HYUP HYUN and SU JIN LEE

Anticancer Research February 2018, 38 (2) 1067-1071;

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