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基于混合元启发式机器学习方法预测和分类肥胖风险

Zarindokht Helforoush1, Hossein Sayyad2

  • 1Department of Mathematics and Systems Engineering, Florida Institute of Technology, Melbourne, FL, United States.

Frontiers in big data
|October 15, 2024
PubMed
概括

机器学习,包括新的ANN-PSO模型,显著提高了肥胖风险预测准确度的92%. 这一进步提供了个性化的医疗保健策略,以打击不断上升的全球肥胖流行病.

关键词:
人工神经网络的人工神经网络粒子集群优化 粒子集群优化超参数调整 超参数调整听算法 (Metaheuristic Algorithms) 是一种算法,可以通过肥胖的分类 肥胖的分类公共卫生公共卫生.

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