Machine learning survival prediction in esophageal cancer using radiomics and body composition from pretreatment and follow-up T12-level computed tomography

doi:10.4251/wjgo.v17.i12.112873

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 17, Issue 12

This Article

(39)

(66)

(0)

(1)

(873)

(3)

Peer-Review Report of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Supplementary Materials of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Journal Information of This Article

Publication Name

World Journal of Gastrointestinal Oncology

ISSN

1948-5204

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Study

World J Gastrointest Oncol. Dec 15, 2025; 17(12): 112873
Published online Dec 15, 2025. doi: 10.4251/wjgo.v17.i12.112873

Full Size Figure Download Figure

Figure 2 Exemplary cross-sectional images of automated segmentations of subcutaneous adipose tissue (brown), visceral adipose tissue (green), and total skeletal muscle area (yellow) at the T12 level.

Citation: Liu MC, Cheng YY, Lin SC, Lin CH, Chuang CY, Chen WH, Liao CH, Hsieh CH, Hsieh MF, Liu YJ. Machine learning survival prediction in esophageal cancer using radiomics and body composition from pretreatment and follow-up T12-level computed tomography. World J Gastrointest Oncol 2025; 17(12): 112873
URL: https://www.wjgnet.com/1948-5204/full/v17/i12/112873.htm
DOI: https://dx.doi.org/10.4251/wjgo.v17.i12.112873

Liu MC, Cheng YY, Lin SC, Lin CH, Chuang CY, Chen WH, Liao CH, Hsieh CH, Hsieh MF, Liu YJ. Machine learning survival prediction in esophageal cancer using radiomics and body composition from pretreatment and follow-up T12-level computed tomography. World J Gastrointest Oncol 2025; 17(12): 112873 [PMID: 41480227 DOI: 10.4251/wjgo.v17.i12.112873]

All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.