الفهرس 
IntroductionOnly 14 pages are availabe for public view
 |  | from | 144 |  |  |
| | | from | 144 | | |
Abstract
This thesis is mainly concerned with the application of artificial
intelligence techniques in healthcare applications. Three applications
are considered in the thesis. The first two applications deal with medical images. In the two applications both COVID-19 detection and tumor detection are considered. Different sophisticated Deep Learning
(DL) models are presented for both purposes. These are compared
with other state-of-the art models. Simulation results on different image datasets ensure superiority of the proposed models.
In addition, the third application is concerned with Electroencephalogram (EEG) signal classification for efficient EEG seizure detection and prediction. The Empirical Mode Decomposition (EMD) is
exploited with statistical attributes for the purpose of EEG signal classification. Simulation results prove superiority of the proposed models
on different datasets. Generally, the presented models for the applications of interest can be exploited in efficient automated diagnosis systems.