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基于XGBoost在胃肠内镜镇静期间的低氧症预测模型

Rong Zhao1,2, Zheng Chen1, Qingyu Teng1

  • 1Department of Anesthesiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Frontiers in medicine
|January 28, 2026
PubMed
概括

这项研究开发了一种AI模型,用于预测镇静性胃肠内镜期间的低氧症. 极端梯度提升 (XGBoost) 模型准确识别有风险的患者,提高程序安全性.

关键词:
在XGBoost上使用.通过内镜检查 (endoscopy) 进行内镜检查低氧症的低氧症是什么机器学习是机器学习.镇静 镇静是一种镇静.

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