iMED: Ubiquitous healthcare platform for chronic patients

Chronic diseases represent a major threat to individuals and communities, as they are the most common diseases and causes of death in the industrial world as well as in the developing countries. According to statistics published by the Center for Disease Control and Prevention, the first five diseases that are most deadly to Americans are chronic diseases that are led by heart diseases that caused 23% of deaths in 2019. As for diabetes, it caused 83,564 deaths in the same year. New infections increase with chronic diseases annually, and the resulting terror increases due to the high number of deaths resulting from it. Our Android application called iMED, the purpose is to improve human's life in general and the chronic patients especially by providing a medical platform that helps them to predict and detect diabetes and cardiovascular diseases. For our first phase (Heart diseases), we used deep learning under python to create a classification model, for the learning of this model we used the MIT-BIH database of PhysioNet. The accuracy of the model is 97.7
%
. In the Diabetic Prevision, the accuracy for PIMA Indians Diabetes Database is 79, 89%. Moreover, since creating a good relationship between the doctor and the patient is the first step in trusting the diagnosis and treatment that the latter is looking for, a smooth communication method has been added between them through text messages, phone calls and video calls.