基于深度学习的实际生存问题应用研究

Application Research on Practical Survival Problems Based on Deep Learning

摘要: 疾病是自古以来一直困扰着所有人类健康甚至是生命的重大难题，生存分析是一种可以模拟患者生存的方法，可以了解感兴趣事件和协变量之间的关系，比如某个癌症病人的死亡时间和他的年龄、性别等协变量的关系。近年来，生存分析的应用越来越广泛，不仅在医院方面，还在电子商务、广告、电信和金融服务等其他行业也获得了很大的发展，通过生存分析方法可以让这些公司更好地了解客户何时购买产品，何时会流失客户，何时会拖欠贷款等。本文使用一种基于深度学习的生存分析模型DeepHit模型处理真实的数据集并与其他模型进行对比，发现DeepHit模型效果良好。

Abstract: Disease is a major problem that has plagued all human health and even life since ancient times. Survival analysis is a method that can simulate the survival of patients, and can understand the relationship between interested events and covariates, such as the relationship between the death time of a cancer patient and his age, gender and other covariates. In recent years, the application of survival analysis has become more and more extensive. It has also achieved great development not only in hospitals, but also in other industries such as e-commerce, advertising, telecommunications and financial services. Through survival analysis, these companies can better understand when customers buy products, when they will lose customers, and when they will default on loans. This paper uses a deep learning based survival analysis model, DeepHit model, to process the real data set and compare it with other models. It is found that DeepHit model has a good effect.