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Updated: Jan 14, 2026

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基于示例学习的强化诱导后低血压预测与交叉重启策略驱动的特征选择

Liufang Sheng1, Shenghui Yu1, Ke Ding2

  • 1The Affiliated People's Hospital, Ningbo University, Ningbo, Zhejiang, 315040, China.

Computer methods and programs in biomedicine
|October 17, 2025
PubMed
概括

一个新的机器学习模型bECRIME-SVM准确地预测了接受手术的老年患者的诱导后低血压 (PIH). 使用这种模型进行早期PIH预测可以改善患者的治疗结果和术后恢复.

关键词:
麻醉剂是一种麻醉剂.临床预测因素 临床预测因素机器学习是机器学习.在诱导后的低血压下.里姆优化算法 里姆优化算法支持矢量机器的支持矢量机器.

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Crossover Experiments01:16

Crossover Experiments

Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
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