基于Doc2Vec和BiLSTM的老年患者疾病预测研究

Disease prediction of elderly patients based on Doc2Vec and BiLSTM

基于电子病历的疾病预测一般是根据病人的症状预测疾病,而很少研究疾病之间的时间顺序关系。引入一种新的电子病历表示法,该表示法考虑了具有时序性的医疗疾病上下文信息,利用Doc2Vec将每种疾病转换成一个类似于其“语义”的数字向量。基于这些向量采用BiLSTM模型来预测老年患者未来的疾病,可以起到对老年疾病的预警作用。最后通过使用真实的医院诊断数据进行实验验证,结果发现模型能够有效地预测出老年人新的疾病,且在保证预测准确率的同时还具有一定的稳定性。

Disease prediction based on electronic medical record generally predicts the disease according to the patient's symptoms,and rarely studies on the time sequence relationship between the diseases.A new representation of electronic medical record is introduced,which considers the context-aware information of medical diseases with time series.Each disease is transformed into a digital vector similar to its"semantics"using Doc2Vec.Based on these vectors,the BiLSTM model is used to predict the potential diseases of elderly patients,which can play an early warning role in diseases of the elderly.Finally,real hospital diagnostic data is used in the experiments,and the results show that the model can effectively predict new diseases of the elderly,and it also has certain stability while ensuring the accuracy of prediction.