… [103] built several configurations upon a distributed deep learning method called SplitNN
[36] to facilitate the health entities collaboratively training deep learning models without …

… SMbased health surveillance systems and still need to be addressed for health informatics. It
… the difficulty of distinguishing between reliable health information and misinformation on SM…

… , treatment, biomedicine, and health informatics. What makes this research outstanding
compared to similar works is that it especially covers the application of deep learning, IoT, and a …

… technique for deep learning to solve 5G problems. This is a technique of deep learning that
is … Next, we see how 5G safety can be improved with machine learning and deep learning. …

… are rapidly growing as medical informatics deals with sensitive data. This work reviews the
… techniques in Healthcare. It first analyzes the need of PPDL in healthcare informatics using a …

… Thus, in this paper, we aim to provide a comparative review of the key deep learning …
deep learning; (3) share some of the best practices for assessing the “goodness” of deep-learning …

… , deep learning eg a convolutional neural network is applied to classify PD; here, the results
show the CNN method outperformed compare to other state-of-the-art machine learning …

… as the deep learning model in the study. The result showed that RBM well obeys the principles
of deep learning … Thus it implies that models with deep architectures are more robust than …

… Overview of Health Informatics Health informatics involves more than merely automating …
With contemporary technology developments in machine learning and deep learning, it is …

… learning applications, however, they have not yet been used extensively in health informatics
… Recent approaches have also used methods like deep learning [15, 16] to uncover the non-…