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使用人工智能预测COVID-19住院和死亡率

Marwah Ahmed Halwani¹, Manal Ahmed Halwani²

¹College of Business, King Abdulaziz University, Rabigh 21589, Saudi Arabia.

Healthcare (Basel, Switzerland)

|September 14, 2024

概括

人工智能 (AI) 模型准确预测COVID-19患者的医院死亡率. 机器学习算法确定了影响患者结果的关键因素,有助于早期疾病管理.

科学领域:

医疗信息学医疗信息学
计算生物学计算生物学
流行病学流行病学

背景情况:

COVID-19对医疗保健系统产生了重大影响,需要准确的预后才能进行有效的治疗,特别是在患有并发症的患者中.
人工智能 (AI) 在医疗保健中越来越多地用于疾病预测,药物开发和流行病预测.
这项研究的重点是应用人工智能来预测COVID-19患者的医院死亡风险.

研究的目的:

开发和评估用于预测COVID-19患者医院死亡率的AI模型.
确定COVID-19中死亡率的关键临床和实验室预测因素.
评估机器学习算法在预测患者结果方面的性能.

主要方法:

使用沙特阿拉伯国王阿卜杜勒阿齐兹大学的数据进行了一项横截面研究.
数据预处理涉及编码分类变量并赋值缺失的值. 医院死亡率是主要结果.
决策树,支持矢量机 (SVM) 和随机森林算法被训练并使用5倍交叉验证进行评估.

主要成果:

包括D-Dimer水平,住院时间和肝功能测试 (ALP,胆红素) 在内的几个因素显著预测了COVID-19死亡率 (p ≤ 0.0001).
机器学习模型显示出强大的预测准确性:决策树 (76%),随机森林 (80%),SVM (82%).
该研究确定了与增加医院死亡风险相关的关键实验室标记物和临床因素.

结论:

人工智能是早期检测和患者监测COVID-19等传染病的重要工具.
由人工智能驱动的算法可以提高治疗的一致性,并支持临床决策,以改善患者护理.
预测模型可以在流行病期间帮助资源分配和管理策略.

关键词:

人工智能的人工智能是人工智能.临床决策支持系统临床决策支持系统疾病的严重程度.死亡率死亡率预测工具预测工具

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