Diagnosis and Prediction Model for COVID19 Patients Response to Treatment based on Convolutional Neural Networks and Whale Optimization Algorithm Using CT Images

Sally M. ELGhamrawy; Abou Ellah Hassanien

To the best of our knowledge, this is the first study to perform prediction on Patient response to COVID-19 treatment. This will lead to saving number of resources and efforts by providing the treatment to non-responding patients. And will help decision makers to search for new treatment for non-responders and give more chance to save the responding cases with appropriate treatment. Number of experiments were performed to validate AIMDP performance. The obtained results proved the promising performance of AIMDP in diagnosing and predicting COVID-19 when compared to recent diagnosing and predicting models. AIMDP achieves high AUC and PPV, and low NPV and execution time, compared to others. As a future work, a plan is made to detect the severity degree of COVID-19 cases to provide appropriate treatment and isolation. Moreover, we plan to collect additional CT scans from different centres to evaluate its performance.