… on machine learning in health informatics. Deep learning, a technique with its foundation
in … , we examine recent health informatics studies that employ deep learning to discuss its …

… concepts and models in deep learning. We reviewed the deep learning models such as RNN…
We also provided detailed case studies of deep learning in healthcare. Challenges faced in …

… that deep learning approaches could be the vehicle for translating big biomedical data
into improved human health. But … Fox Foundation. The press release can be found at https://www.…

… Machine Learning (ML) studies algorithms which can learn from data to gain knowledge
from experience and to make decisions and predictions. Health Informatics (HI) studies the …

… various aspects of health informatics in detail, including what is health informatics, the range
of applications, and delineating how the application of informatics in healthcare makes a …

… the foundations of deep learning and its applications to health informatics. It covers … This
chapter compares 14 different deep learning models with four classifiers to diagnose COVID-19 …

… In this study, the Radial Basis Function (RBF) kernel was used for classification. The RBF
can be denoted as \(K\left( {\chi , {\Upsilon }} \right) = exp\left( { - \frac{{\left\| {\chi - {\Upsilon }^{2} …

… using a support vector machine (SVM) along with a radial basis function which improves …
The most popular algorithms of classification used in health informatics are CART, C4.5, C5.…

… Deep learning, a technique with its foundation in artificial … In this paper, a review of recent
health informatics studies has been done that employ deep learning to discuss its relative …

… Combined with computational modeling and the development of distributed databases,
clinical data is being archived and analyzed using machine learning techniques and data mining…