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Updated: Jul 28, 2025

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集成IDPC集群分析和可解释机器学习,用于预测ESCC患者的生存风险

Dan Ling1, Anhao Liu1, Junwei Sun1

  • 1Henan Key Lab of Information-Based Electrical Appliances, Zhengzhou University of Light Industry, Zhengzhou, 450002, China.

Interdisciplinary sciences, computational life sciences
|May 29, 2023
PubMed
概括

本研究引入了一种可解释的食道状细胞癌 (ESCC) 的生存风险预测模型,使用WOA-XGBoost和SHAP. 这种新的方法提高了预测准确性和可解释性,从而改善了患者的预后.

关键词:
食管状细胞癌的癌症改进了DPC的功能这就是 SHAP SHAP 的意思.预测生存的预测.在XGBoost中使用.

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