Machine Learning Pipeline for the Automated Prediction of MicrovascularInvasion in HepatocellularCarcinomas

Machine Learning Pipeline for the Automated Prediction of MicrovascularInvasion in HepatocellularCarcinomas

<b>Background:</b> Microvascular invasion (MVI) is a necessary step in the metastatic evolution of hepatocellular carcinoma liver tumors. Predicting the onset of MVI in the initial stages of the tumors could improve patient survival and the quality of life. In this study, the possibility...

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Bibliographic Details
Main Authors: Riccardo Biondi, Matteo Renzulli, Rita Golfieri, Nico Curti, Gianluca Carlini, Claudia Sala, Enrico Giampieri, Daniel Remondini, Giulio Vara, Arrigo Cattabriga, Maria Adriana Cocozza, Luigi Vincenzo Pastore, Nicolò Brandi, Antonino Palmeri, Leonardo Scarpetti, Gaia Tanzarella, Matteo Cescon, Matteo Ravaioli, Gastone Castellani, Francesca Coppola
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Applied Sciences
Subjects:
radiomics
artificial intelligence
machine learning
medical imaging
survival
Online Access:https://www.mdpi.com/2076-3417/13/3/1371

Internet

https://www.mdpi.com/2076-3417/13/3/1371

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