… and health informatics, and deep learning will be highly benefited. This book would be a
good collection of state-of-the-art approaches for deep learning based biomedical and health …

… health care features. Thus this book chapter deals with detailed analysis of various deep
learning approaches in health informatics… and their applications in the health care domain. Also …

… applied to health informatics is presented. We begin by introducing some common non-deep
learning models used in many studies to compare or combine with deep learning models. …

… 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 …

… This study uses deep learning methods to analyze the EEG signals of athletes. It then proposes
and designs a channel attention module connected to the input layer of the convolutional …

… 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 …

… 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, …

… During the past few years, medical imaging informatics has made … deep learning (DL)
techniques [2]. However, fundamental challenges hinder the effective deployment of deep learning …

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

… , realizing deep learning models that generalize across healthcare … learning can enable
collaborative training of deep learning models across disparate and privately maintained health …