##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.