Computing technique is one of the key technologies that is being currently used to perform
medical diagnostics in the healthcare domain, thanks to the abundance of medical data being …

… these are used, machine learning, especially, deep learning techniques that are applied
is … health informatics applications are summarized that employs different deep learning …

… health records may become laborious. As a result, deep learning can be used to keep track
of smart health … of real-time health data, and deep learning can assist in effectively monitoring …

… the fields of biomedical and health informatics are complex and heterogeneous. The data
with various types including medical imaging, clinical genomics, electronic health record (EHr) …

… informaticians should become familiar with machine learning and deep learning. Additionally,
they should have a strong background in data analytics and data visualization to use, …

… of Deep Learning applications for Biomedical Engineering and Health Informatics, including
Deep Learning for … Deep Learning applied to Electronic Health Records (EHR), including …

… deep learning for healthcare has grown for two reasons. First, for healthcare researchers,
deep learning models yield better performance in many tasks than traditional machine learning …

… Like Gradient Descent and Adam, there are many more state-of-theart optimization algorithms
currently in use for deep learning, but they are not discussed here as they are not relevant …

… [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…