基于无监督深度学习的电子健康档案数据挖掘技术研究进展

Research Progress of Electronic Health Record Data Mining Based on Unsupervised Deep Learning

介绍自编码器、生成式对抗网络、BERT等无监督深度学习方法,阐述其在电子健康档案数据挖掘中的应用以及存在的挑战,指出无监督深度学习技术能够加速医疗知识发现和临床决策支持,促进个性化医学发展。

The paper introduces unsupervised deep learning methods such as autoencoder,Generative Adversarial Network(GAN)and BERT and their applications and challenges in Electronic Health Record(EHR)data mining,and points out that unsupervised deep learning technology improves the efficiency of medical knowledge discovery and clinical decision support and promotes the development of personalized medicine.