Deep Learning Approach for Designing and Development of Risk Level Indicator for Patients with Lung Diseases

Abstract

"Lung disease" as a medical term, discusses as several disorders that affects both lungs. There are different types of lung disease like Asthma, lungs infections like Influenza, Pneumonia, Tuberculosis, and numerous other types of breathing problems including Lung cancers. These lung diseases can be the main reason for failure in breathing. Due to COVID19 pandemic, Pneumonia and COVID19 were highlighted mostly as fatal diseases if not detected on time. Newly identified COVID19 diseases has caused many deaths and confirmed detections reported worldwide, followed with a greatest risk to community wellbeing, especially for patients with lung diseases. Process of developing a clinically accepted vaccine or specific therapeutic drug for this disease are not finalized, which will contribute to the expansion of actual prevention action plans. Thus, methods to detect lung illness accurately and efficiently is important. Proposed solution will easily and precisely detect the risk level of patients with these two lung diseases Pneumonia and COVID19 using a mobile application with chest radiography (Chest X-rays), which is considered as a cheap, easy to access and speedy manner. Proposed solution will identify, classify and evaluate the risk level of the patient suffering with the use of Image Processing, Machine Learning techniques and Convolutional Neural Networks. So, anybody who use the proposed solution may have the ability to have a precious decision about own medical condition accurately, quickly with low cost. Proposed solution can calculate severity level of a patient with more than 97% accuracy with chest radiography analysis together with patient’s current symptoms and breath holding time evaluation.