Predictive Value of <sup>18</sup>F-FDG PET/CT Using Machine Learning for Pathological Response to Neoadjuvant Concurrent Chemoradiotherapy in Patients with Stage III Non-Small Cell Lung Cancer

Predictive Value of <sup>18</sup>F-FDG PET/CT Using Machine Learning for Pathological Response to Neoadjuvant Concurrent Chemoradiotherapy in Patients with Stage III Non-Small Cell Lung Cancer

We investigated predictions from <sup>18</sup>F-FDG PET/CT using machine learning (ML) to assess the neoadjuvant CCRT response of patients with stage III non-small cell lung cancer (NSCLC) and compared them with predictions from conventional PET parameters and from physicians. A retrospe...

Full description

Bibliographic Details
Main Authors: Jang Yoo, Jaeho Lee, Miju Cheon, Sang-Keun Woo, Myung-Ju Ahn, Hong Ryull Pyo, Yong Soo Choi, Joung Ho Han, Joon Young Choi
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Cancers
Subjects:
non-small cell lung cancer
neoadjuvant concurrent chemoradiotherapy
<sup>18</sup>F-FDG PET/CT
machine learning
random forest
pathologic complete response
Online Access:https://www.mdpi.com/2072-6694/14/8/1987

Internet

https://www.mdpi.com/2072-6694/14/8/1987

Similar Items