A Parliamentary Framework for Missing Data Imputation using LSTM Model

abdulaziz saleh


Healthcare prediction system plays main role in offering better health care services.it enable the decision maker of health institutions to take the proper decisions in proper time.    since the rapid increasing of electronic health records(HER), it become more challenge to analysis and get advantages of such data. So enhancing quality of training data is a common condition that has considerable impact on the performance of health care prediction system.  However, using    incomplete dataset to train these systems leads to low accurate results and makes the prediction process more complex.   This paper proposes a conceptual model for missing data imputation using LSTM model.  This model extends an existed prediction model and show how LSTM model is integrated with other layers of health care prediction system


  • There are currently no refbacks.

Copyright (c) 2019 abdulaziz saleh

© 2016 JTeC. All Rights Reserved    |    UniKL MIIT