一种基于深度学习的献血者精准招募方法

Precise blood donor recruitment method based on deep learning

深度学习是一种可以学习无序样本数据内在规律的新方法,可以实现献血者的精准招募,从而提高招募效率并解决血液短缺的问题。文章将2021—2022年16628名收到短信和电话招募的献血者作为研究对象,对数据进行了关联分析与特征提取,引入了对照组模型进行实验。结果表明,基于深度学习方法的献血者精准招募方法的准确性是传统方案的2.1倍,且招募效率提升了110%,有助于卫生部门在面临突发情况时保障血液供应。

Deep learning is a new method that can learn the inherent rules of unordered sample data,enabling precise recruitment of blood donors,thereby improving recruitment efficiency and solving the problem of blood shortage.The article takes 16628 blood donors recruited through text messages and phone calls from 2021—2022 as the research subjects,conducts correlation analysis and feature extraction on the data,and introduces a control group model for experimentation.The results show that the accuracy of the precise recruitment method for blood donors based on deep learning methods is 2.1 times that of traditional methods,and the recruitment efficiency has been improved by 110%,