##Statistics Seminar##\\ Department of Mathematical Sciences ^ **DATE:**|Thursday, October 7, 2021 | ^ **TIME:**|1:15pm -- 2:15pm | ^ **LOCATION:**|Zoom meeting | ^ **SPEAKER:**|Yifei Zeng, Binghamton University | ^ **TITLE:**|A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images | \\ **Abstract** In this study, they propose CoroNet, a Deep Convolutional Neural Network model to automati- cally detect COVID-19 infection from chest X-ray images. CoroNet achieved promising results on a small prepared dataset which indicates that given more data, the proposed model can achieve better results with minimum pre-processing of data. Overall, the proposed model substantially advances the current radiology based methodology and during COVID- 19 pandemic, it can be a very helpful tool for clinical practitioners and radiologists to aid them in diagnosis, quantification and follow-up of COVID-19 cases.