Development and Validation of Artificial-Intelligence-Based Radiomics Model Using Computed Tomography Features for Preoperative Risk Stratification of Gastrointestinal Stromal Tumors

Development and Validation of Artificial-Intelligence-Based Radiomics Model Using Computed Tomography Features for Preoperative Risk Stratification of Gastrointestinal Stromal Tumors

Background: preoperative risk assessment of gastrointestinal stromal tumors (GISTS) is required for optimal and personalized treatment planning. Radiomics features are promising tools to predict risk assessment. The purpose of this study is to develop and validate an artificial intelligence classifi...

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Bibliographic Details
Main Authors: Marco Rengo, Alessandro Onori, Damiano Caruso, Davide Bellini, Francesco Carbonetti, Domenico De Santis, Simone Vicini, Marta Zerunian, Elsa Iannicelli, Iacopo Carbone, Andrea Laghi
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Journal of Personalized Medicine
Subjects:
gastrointestinal stromal tumor
radiomics
machine learning
risk assessment
prognostic
artificial intelligence
Online Access:https://www.mdpi.com/2075-4426/13/5/717

Internet

https://www.mdpi.com/2075-4426/13/5/717

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