… part of deep learning. In this paper, deep learning for IoT applications in health care systems
… This paper elaborated on several technical methods in order to boost IoT in the healthcare …

… the significance of deep learning and the various deep learning techniques and networks. …
Deep learning [8] is one of the machine learning methods that dominate in various application …

… The deep learning approach is a subset of machine learning stimulated by the human brain’s
data processing pattern [1, 3,4,5,6,7,8, 13,14,15,16]. The Venn diagram in Fig. 1 shows the …

… Such models will be referred to as complex-based methods … machine learning, and is suitable
to screen very large databases, see for example Pharmit [18]. However, these methods are …

… The current AI is based on machine learning. The model (network) for a specific task (eg, …
use of the trained model. In conventional machine learning (non-Deep Learning) approaches, …

… major limitations of deep learning in medical image analysis. … deep learning-based
computer-aided diagnosis applications … and theoretical approaches of deep learning-based …

… tasks, where deep learning approaches were able to outperform the standard methods,
including image processing and analysis [2,3]. Moreover, deep learning delivers reasonable …

… language processing, and even medicine. In this article, we provide a review of the methods
and applications of machine learning and deep learning, including their strengths and …

… , machine learning (ML) and deep learning (DL) have been widely used in our everyday lives
in a number of ways. … and DL methods for COVID-19 diagnosis and treatment. Furthermore, …

… Next, we discuss several example medical imaging applications that stand to … medical video,
highlighting ways in which clinical workflows can integrate computer vision to enhance care…