Machine Learning Models Derived from [<sup>18</sup>F]FDG PET/CT for the Prediction of Recurrence in Patients with Thymomas

Machine Learning Models Derived from [<sup>18</sup>F]FDG PET/CT for the Prediction of Recurrence in Patients with Thymomas

<b>Background/Objectives:</b> This study aimed to develop machine learning (ML) models to predict recurrence in thymoma patients using conventional and radiomic signatures extracted from preoperative [<sup>18</sup>F]FDG PET/CT. <b>Methods:</b> A total of 50 patien...

Full description

Saved in:
Bibliographic Details
Main Authors: Angelo Castello, Luigi Manco, Margherita Cattaneo, Riccardo Orlandi, Lorenzo Rosso, Giorgio Alberto Croci, Luigia Florimonte, Giovanni Scribano, Alessandro Turra, Stefano Ferrero, Mario Nosotti, Gianpaolo Carrafiello, Massimo Castellani, Paolo Mendogni
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Bioengineering
Subjects:
thymomas
FDG
PET/CT
recurrence
radiomics
machine learning
Online Access:https://www.mdpi.com/2306-5354/12/7/721
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2306-5354/12/7/721

Similar Items