Evaluation of Recurrent Neural Network Model Training for Health Care Suggestions

Abstract

Neural networks have revolutionized the field of data analytics and decision support, where recurrent neural networks are designed for solving time-series data. Total care is a synonym for complete patient care recently to respond patient’s physical, emotional, social, economic, and spiritual needs, and as such an efficient prediction system for total care suggestions could help physicians and other healthcare providers in making clinical judgement. Therefore, this study aims to compare neural network models on predicting patients in need of the total care. The experimental results show that the LSTM (long short-term memory) prediction model outperforms other neural network models on forecasting total care needs.