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Updated: Jun 21, 2025
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机器学习在预测成人和老年人的肥胖症方面是否具有很高的性能? 一个系统的审查和元分析
Felipe Mendes Delpino1, Ândria Krolow Costa2, Murilo César do Nascimento3
1Postgraduate Program in Nursing, Federal University of Pelotas. Pelotas, Rio Grande do Sul, Brazil; Postgraduate Program in Public Health Nursing, University of São Paulo, Ribeirão Preto, Brazil.
概括
机器学习模型在肥胖预测方面显示出有希望的结果. 随机森林和物流回归算法表现最好,ROC曲线下的面积 (AUC) 超过0.85.
科学领域:
- * 医学信息学 医学信息学
- * 计算生物学 * 计算生物学
- * * 公共卫生 公共卫生
背景情况:
- * 肥胖是一个日益严重的全球健康问题,需要有效的预测工具.
- *机器学习 (ML) 为开发准确的肥胖预测模型提供了潜力.
结论:
- * ML模型是预测肥胖的有效工具.
- *未来的研究应该专注于使用标准化,更大的数据集,并探索更广泛的ML算法.
- * 持续开发用于肥胖预测的ML可以帮助早期干预和公共卫生战略.
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