A deep learning prediction model using sparse stacked denoising autoencoders with a softmax layer and logistic regression outperformed other machine learning methods in predicting hospital outpatient non-attendance.
Does a deep learning approach based on sparse stacked denoising autoencoders improve the prediction of non-attendance in hospital outpatient appointments compared to other machine learning models?
A deep learning model using sparse stacked denoising autoencoders outperforms traditional machine learning models in predicting hospital outpatient non-attendance.
The hospital outpatient non-attendance imposes a substantial financial burden on hospitals and roots in multiple diverse reasons. This research aims to build an advanced predictive model for predicting non-attendance regarding the whole spectrum of probable contributing factors to non-attendance that could be collated from heterogeneous sources including electronic patients records and external non-hospital data. We proposed a new non-attendance prediction model based on deep neural networks and machine learning models. The proposed approach works upon sparse stacked denoising autoencoders (SDAEs) to learn the underlying manifold of data and thereby compacting information and providing a better representation that can be utilised afterwards by other learning models as well. The proposed approach is evaluated over real hospital data and compared with several well-known and scalable machine learning models. The evaluation results reveal the proposed approach with softmax layer and logistic regression outperforms other methods in practice.
Dashtban et al. (Mon,) conducted a other in Hospital outpatient non-attendance. Deep learning prediction model (sparse stacked denoising autoencoders) vs. Other machine learning models was evaluated on Prediction of non-attendance. A deep learning prediction model using sparse stacked denoising autoencoders with a softmax layer and logistic regression outperformed other machine learning methods in predicting hospital outpatient non-attendance.