Table 1_Machine learning-based differentiation of lung squamous cell carcinoma and adenocarcinoma using clinical-semantic and radiomic features.docx
Purpose<p>To evaluate and compare the predictive performance of machine learning methods using clinical-semantic, radiomic, and combined features in distinguishing squamous cell carcinoma (SCC) from adenocarcinoma (ADC) in non-small cell lung cancer (NSCLC).</p>Methods<p>A total of...
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| Hovedforfatter: | Yanju Li (9697993) (author) |
|---|---|
| Andre forfattere: | Xiaomeng Yang (702951) (author), Yingjin Zhang (20532682) (author), Jing Liang (32441) (author), Jiaxin Liu (833821) (author), Xinru Zheng (16801562) (author), Jing Wang (6206297) (author), Zhaoxiang Ye (4468483) (author) |
| Udgivet: |
2025
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Table 1_Multi−cohort validation based on coagulation-related genes for predicting prognosis of esophageal squamous cell carcinoma.xlsx
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Additional file 13 of Development of a cancer metastasis-associated risk model via multi-machine-learning algorithms for prognostic risk evaluation and clinical application in oral squamous cell carcinoma
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