The main idea of this project is to detect COVID-19 and pneumonia and discriminate between them. COVID-19 is an infectious disease that mainly affects the lungs. Pneumonia is also an infection that causes inflammation in the air sacs in lungs. COVID-19 and pneumonia have similar symptoms in the lungs as breathing problems that appear in CT as ground-glass opacity (GGO). For discrimination between them, we are using a dataset that consists of three classes (COVID-19, Pneumonia, Normal lungs). By using deep learning techniques (CNN Model), which will facilitate diagnosing these diseases efficiently and in a shorter time, it is expected to provide better results compared to other techniques. For determining the severity of both diseases, we are using clustering with Deep Learning algorithms. Also, for COVID-19 detection we are using a dataset that contains 6 blood tests labeled by PCR test. These tests will be classified by machine learning algorithms.

The main goal of our system is to detect COVID-19 with high accuracy and discriminate between it and Pneumonia from CT images and detect COVID-19 from the 6 blood (CBC, CRP, D.DIMER, S.Ferritin, LDH, ALT) tests also to be more accurate, and classify the severity of both diseases in lungs. Another goal we aim to help doctors and patients by making the interface of the system user friendly (easy to use).

The development of this system focuses on helping COVID-19 and Pneumonia patients and doctors of this field because the two diseases have similar symptoms. The system will detect both diseases (COVID-19,Pneumonia) from CT images and discriminate between them using deep learning techniques. Also the system will classify the severity of the two diseases which affect the lungs. In addition to, the system will detect COVID-19 from blood tests which are labeled by PCR test. This system is a web application that can by accessed everywhere and anytime by patients and doctors. Users of this system must have an account on system to use it.