الفهرس 
An Intelligent Diagnostic Prediction System in Healthcare
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Abstract
This thesis introduces an intelligent diagnostic prediction framework for COVID-19 severity levels. The framework includes two parts: the first one is an intelligent diagnosis model for detecting patient’s severity levels, and the second is an enhanced intelligent diagnosis model to consider time factor by identifying the most suitable time besides detecting the patient’s severity. The frameworks can predict different levels of a patient’s severity, like whether the patient needs to enter the Intensive Care Unit (ICU) or not, as well as report his death. The frameworks can handle heterogeneous patient data like X-ray images and clinical blood data. Various experiments have been applied on the models and the results prove the ability of the models to improve some of healthcare problems by predicting patient’s severity and assisting doctors in decision-making to saving patients’ live.