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Updated: Jul 1, 2025

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一个强大的框架,用于增强心血管疾病风险预测,使用优化的类别增强模型.

Zhaobin Qiu1, Ying Qiao1,2, Wanyuan Shi1

  • 1School of Mathematics and Information Sciences, North Minzu University, Yinchuan, China.

Mathematical biosciences and engineering : MBE
|March 8, 2024
PubMed
概括

一个新的机器学习框架,CVD-OCSCatBoost,准确预测心血管疾病 (CVD) 的风险. 这种方法增强了对心血管疾病的早期检测和干预策略,改善了患者的治疗结果.

关键词:
在 CatBoost 中使用 CatBoost.心血管疾病心血管疾病的搜索算法 的搜索算法基于反对的学习是基于反对的学习.

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