Machine Learning and Radiomics Applications in Esophageal Cancers Using Non-Invasive Imaging Methods—A Critical Review of Literature

Machine Learning and Radiomics Applications in Esophageal Cancers Using Non-Invasive Imaging Methods—A Critical Review of Literature

Esophageal cancer (EC) is of public health significance as one of the leading causes of cancer death worldwide. Accurate staging, treatment planning and prognostication in EC patients are of vital importance. Recent advances in machine learning (ML) techniques demonstrate their potential to provide...

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Bibliographic Details
Main Authors: Chen-Yi Xie, Chun-Lap Pang, Benjamin Chan, Emily Yuen-Yuen Wong, Qi Dou, Varut Vardhanabhuti
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Cancers
Subjects:
machine learning
esophageal neoplasms
radiology
Online Access:https://www.mdpi.com/2072-6694/13/10/2469

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