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--- seminars:stat:211007 [2021/09/30 01:46] – qyu
+++ seminars:stat:211007 [2021/10/02 22:16] (current) – qyu
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+<WRAP centeralign>##Statistics Seminar##\\ Department of Mathematical Sciences</WRAP>
+<WRAP 70% center>
+^  **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  |
+</WRAP>
+\\
+<WRAP center box 80%>
+<WRAP centeralign>**Abstract**</WRAP>
+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.
+</WRAP>