基于机器学习的患者缴费行为研究

Study on payment behavior of patients based on machine learning

目的:通过使用机器学习技术对医院患者进行用户画像和缴费行为预测,提升患者就诊体验。方法:通过获取患者、自助设备等静态、动态数据后,利用数据挖掘技术进行数据预处理和数据分析,搭建全连接神经网络模型预测患者缴费行为。结果:对患者进行画像,分析缴费行为,并提出一种基于机器学习的患者缴费行为预测方法。结论:通过用户画像和数据分析,可有效提高医疗资源利用率和优化医院服务水平。

Objective To improve patient experience by predicting user portrait and payment behavior with the machine learning technology.Methods After obtaining static and dynamic data of patients and self-service devices,data preprocessing and data analysis were carried out by using the data mining technology,and a fully connected neural network model was built to predict the payment behavior of patients.Results The portrait of patients was made,payment behavior was analyzed,and a prediction method of payment behavior of patients based on machine learning was proposed.Conclusion The fully connected neural network model based on user portrait and data analysis can effectively increase the utilization rate of medical resources and raise the service level of the hospital.