Development of High-Resolution Dedicated PET-Based Radiomics Machine Learning Model to Predict Axillary Lymph Node Status in Early-Stage Breast Cancer

Development of High-Resolution Dedicated PET-Based Radiomics Machine Learning Model to Predict Axillary Lymph Node Status in Early-Stage Breast Cancer

Purpose of the Report: Accurate clinical axillary evaluation plays an important role in the diagnosis and treatment planning for early-stage breast cancer (BC). This study aimed to develop a scalable, non-invasive and robust machine learning model for predicting of the pathological node status using...

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Bibliographic Details
Main Authors: Jingyi Cheng, Caiyue Ren, Guangyu Liu, Ruohong Shui, Yingjian Zhang, Junjie Li, Zhimin Shao
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Cancers
Subjects:
breast cancer
axillary lymph node status
18F-FDG dedicated PET
radiomics
machine learning
Online Access:https://www.mdpi.com/2072-6694/14/4/950

Internet

https://www.mdpi.com/2072-6694/14/4/950

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