Machine learning-based dynamic CEA trajectory and prognosis in gastric cancer

Higher CEA trajectories are associated with a worse prognosis, highlighting the importance of enhanced monitoring for this group of patients.

Authors

Institutions

Publication Details

Journal
BMC Cancer
Published
2025-07-26
DOI
https://doi.org/10.1186/s12885-025-14623-w
Citations
2
Primary Topic
Gastric Cancer Management and Outcomes
Type
article
Field-Weighted Citation Impact
3.04

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article

Machine learning-based dynamic CEA trajectory and prognosis in gastric cancer

Yonghe Chen, Junjie Liu, Lei Lian, Dan Liu et al.
2 citations
BMC Cancer
Gastric Cancer Management and Outcomes
3.04
article

Machine learning-based dynamic CEA trajectory and prognosis in gastric cancer

Yonghe Chen, Junjie Liu, Lei Lian, Dan Liu, Zhong Lin Wang, Yi Lin, Xiaohan Jiang
article en
2 citations

Abstract

Higher CEA trajectories are associated with a worse prognosis, highlighting the importance of enhanced monitoring for this group of patients.

BMC CancerVol. 25(1)
Guangzhou University of Chinese Medicine (CN), Sun Yat-sen University (CN), Sixth Affiliated Hospital of Sun Yat-sen University (CN)
National Natural Science Foundation of China, Natural Science Foundation for Young Scientists of Shanxi Province, Young Scientists Fund
Good health and well-being
Openalex Percentile: Top 8%
Gastric Cancer Management and Outcomes
3.04
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Machine learning-based dynamic CEA trajectory and prognosis in gastric cancer — Yonghe Chen, Junjie Liu, et al. · BMC Cancer (2025) | TGRS Research Map | TGRS