Transfer Learning Technique for Covid-19 Screening from CT-Scan: An Empirical Approach

Abstract

As a result of the Covid-19 pandemic, the field of Medical Sciences has been challenged with new challenges and benchmarks for development. Front line workers are overcoming the Covid-19 challenge with four steps: Screening and Diagnosis, Contact Tracing, Drug and Vaccine Development, and Prediction & Forecasting. Following the above segments carefully can save millions of lives. Artificial Intelligence has proven invaluable in predicting critical factors in many fields. With the ability of AI to process huge databases and conclude with high precision, we are motivated to use AI to screen and diagnose the Covid-19 pandemic. This paper examines the strategic use of Transfer Learning for screening and diagnosis of Covid-19 Patients. The Xception model is used to categorize Covid-19 infected patients. Our proposed Xception model has achieved better Accuracy, Sensitivity and Specificity as compared with state-of-the-art models.