Artificial Intelligence Applications on Restaging [¹⁸F]FDG PET/CT in Metastatic Colorectal Cancer: A Preliminary Report of Morpho-Functional Radiomics Classification for Prediction of Disease Outcome

The aim of this study was to investigate the application of [¹⁸F]FDG PET/CT images-based textural features analysis to propose radiomics models able to early predict disease progression (PD) and survival outcome in metastatic colorectal cancer (MCC) patients after first adjuvant therapy....

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Bibliografiske detaljer

Principais autores:	Pierpaolo Alongi, Alessandro Stefano, Albert Comelli, Alessandro Spataro, Giuseppe Formica, Riccardo Laudicella, Helena Lanzafame, Francesco Panasiti, Costanza Longo, Federico Midiri, Viviana Benfante, Ludovico La Grutta, Irene Andrea Burger, Tommaso Vincenzo Bartolotta, Sergio Baldari, Roberto Lagalla, Massimo Midiri, Giorgio Russo
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2022-03-01
Serier:	Applied Sciences
Fag:	colon cancer radiomics artificial intelligence positron emission tomography-computed tomography nuclear medicine
Online adgang:	https://www.mdpi.com/2076-3417/12/6/2941
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