… Thus, a combination of deep learning and radiomics may help evaluate the image … deep
learning radiomics model to identify poor outcomes in COVID-19 patients with underlying health …

… deep learning technology breakthroughs. Therefore, the current study aims to examine the
most recent research on the use of deep learning techniques for dental informatics … healthcare …

… The fields of medicine science and health informatics have … of machine learning and deep
learning applications play a … using data mining and deep learning approaches for analyzing …

… That is, deep learning was used for surveillance in general health management [56,59]
and … deep learning in these systems aims to accurately predict and assist patients with self-health …

… Here, the advantages and disadvantages of several deep learning methods such as an RNN,
deep belief networks are well described. This work also discussed different applications of …

… In this paper, we apply deep learning on a set of 57 EEG features extracted from a maximum
of two EEG channels to accurately differentiate between patients with insomnia or controls …

… It then provides a synopsis of contemporary and emerging algorithmic methods for disease
classification and organ/ tissue segmentation, focusing on AI and deep learning architectures …

… health informatics safety supervision (UAHISS) system based on medical imaging and deep
learning … (2) We design the novel DL system for the health informatics application scenarios. …

… Health Informatics and Healthcare using AI and Smart Computing. There are numerous fields
within the healthcare … Computing, Deep Learning, and Data Analysis in the field of Health …

… K-means clustering and deep learning, though deep learning can also be used unsupervised.
… Deep learning employs neural networks and classification algorithms to make predictions …