… Machine learning and deep learning artificial intelligence (AI) models are playing a beneficial
role in health informatics. But the use cases are not limited to medical research; they can …

… domain has been ever-expanding especially since the community embraced the era of deep
learning, which provides the ground to develop, validate, and advance large AI models for …

… , transfer learning, and multi-agent hybrid systems. The article concludes with emphasizing
… health informatics, as well as the successful application of ML for solving health informatics …

… The algorithm based on deep learning … of deep learning in biomedical informatics alongside
human services. We trust that this part gives a diagram of the utilization of deep learning …

… You do not need to program it explicitly for its functions, it can learn on its own like humans.
Artificial intelligence works on its subsets such as machine learning and deep learning which …

… deep learning technologies to advance the health care domain. Based on the analyzed work,
we suggest that deep learning … biomedical data into improved human health. However, we …

… In conclusion, the integration of deep learning in health informatics for image-based disease
diagnosis is transforming the landscape of medical imaging and disease management. The …

… Amongst the deep learning applications, this thesis focuses on problems in health informatics.
Compared to the general deep learning applications, health informatics problems are …

… In this paper, we have developed a healthcare informatics system to investigate and detect
the gallstones present. A detailed comparison of different algorithms inspired by cutting edge …

… deep learning to clinical tasks based on EHR data, where we find a variety of deep learning
… including information extraction, representation learning, outcome prediction, phenotyping, …