Abstract
Chronic Obstructive Pulmonary Disease (COPD) becomes highly prevalent disease that impacts both patients and healthcare system. Patients in the advanced stages of COPD can be vulnerable to acute exacerbations that can be fatal. The exacerbations can affect hospitals' resources caused by frequent admissions and readmissions. Caregivers want a reliable mechanism that can help them manage COPD patients remotely and predict the risks of exacerbation in advance before COPD episode is about to occur. It is vital to develop effective tools to provide much-needed assistance for the elderly COPD patients. Tools involve understanding the patient's behavior and providing indicators that assist the decision-making process. In this paper, I discuss the design and implementation of a feed forward multi-layer neural network for prediction of COPD acute exacerbations. I used the backpropagation algorithm to train the ANN network. The results show a positive correlation between the computed outputs and the desired outputs with respect to COPD Clinical Questionnaire.