Machine learning–based response assessment in patients with rectal cancer after neoadjuvant chemoradiotherapy: radiomics analysis for assessing tumor regression grade using T2-weighted magnetic resonance images
Crossref DOI link: https://doi.org/10.1007/s00384-024-04651-6
Published Online: 2024-05-24
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Lee, Yong Dae
Kim, Hyug-Gi
Seo, Miri
Moon, Sung Kyoung
Park, Seong Jin
You, Myung-Won
Text and Data Mining valid from 2024-05-24
Version of Record valid from 2024-05-24
Article History
Accepted: 17 May 2024
First Online: 24 May 2024
Declarations
:
: The authors declare no competing interests.