A New Classification Model Based on Stacknet and Deep Learning for Fast Detection of COVID 19 Through X Rays Images

Jalal RABBAH, Mohammed RIDOUANI, Larbi HASSOUNI
2020 2020 Fourth International Conference On Intelligent Computing in Data Sciences (ICDS)  
Coronavirus (COVID-19) is continuing its spread across the world, with more than seven million confirmed cases. The findings could be important as lockdown restrictions begin to be eased, and they highlight the need for the introduction of increasingly effective techniques to deal with this spread and help effectively identify new infections more quickly, at a reasonable cost and with a minimum error rate. The use of machine learning models constitutes a new approach, used more and more in this
more » ... re and more in this field. In this proposed work, we built a new classification model named CovStacknet and it based on StackNet metamodeling methodology combined with deep convolutional neural network as the basis for features extraction from X-Ray images. The proposed model has reached an accuracy score of 98%, which is better than that achieved by the basic models.
doi:10.1109/icds50568.2020.9268777 fatcat:mjj7wmdskjbnnjqe5pyutfaj4q