… data with a guidance of relevant clinical questions to assist clinical decision-making and in
turn provides the physicians the analysis … of deep learning for predictive analysis in the health …

… Hence, reliable and efficient methods for healthcare predictive analysis are essential. … of
existing machine learning and deep learning approaches utilized in healthcare prediction and …

… deep learning approaches could be the vehicle for translating big biomedical data into improved
human health. … the capabilities of deep learning for health care data analysis as well. In …

… It can learn from a few shots of historical healthcare data to make either binary or multi-label
predictions. … of our deep learning-based predictive model in supporting healthcare analytics. …

… predictive analytics can be classified into machine learning techniques and regression
techniques. Machine learning … popular in conducting predictive analytics due to their outstanding …

… Predictive modeling is also known as predictive analytics … A predictive model in healthcare
learns the historical data of … In this review, the use of deep learning models such as LSTM/…

… The results also show that our solution outperforms many existing machine learning
models, especially when data are complex. It is important to note that, although we conducted …

… while coping with the data sufficiency constraint. We propose a deep learning–based method
… This study offers several implications for health informatics and improved acute disease …

… analysis technique in the research area of machine learning, deep learning, and the healthcare
… And it revealed the worldwide research trends and performance analysis of the subject …

… machine learning and predictive analytics are making a significant impact.Early detection and
diagnosis benefit from machine learning … information, and imaging data. These algorithms …