ArticleTranslational cancer research2025
Predictive value of CT-based imaging model for
Article in Translational cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Review
- Development and validation of a machine learning-based prognostic model using mitochondrial dysfunction-related genes for colorectal cancer patients.Translational cancer research · 2025Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: In colorectal cancer, the Methods: Patients with colorectal cancer treated in National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital from May 2022 to December 2023 were divided into mutation group and non-mutation group according to the occurrence of Results: In total, 100 patients were selected. Univariate analysis and multivariate logistics regression analysis showed that lymph node metastasis, tumor differentiation, tumor invasion depth and tumor size were independent influencing factors of Conclusions: In this study, the CT-based radiomics nomogram was constructed and its value was analyzed. The imaging model of CT is of high value in predicting
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Registered trials
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