报告人：Yudong Zhang (University of Leicester)
报告题目：AI Theories and Methods for COVID-19 Recognition
报告时间：2022年12月14日 18:30
报告地点：腾讯会议893-888-218
报告摘要：COVID-19 is a pandemic disease that caused more than 6.60 million deaths until 13/Nov/2022. X-ray and CT scans are two popular medical imaging technique used in radiology to get detailed images of the body noninvasively for diagnostic purposes. Traditional manual labeling of X-ray or CT-based scans is tedious and error-prone. To solve the problem, our lab develops or applies new AI theories and methods, such as transfer learning, advanced pooling-based networks, graph convolutional networks, attention neural networks, weakly supervised networks, etc. We also use cloud computing techniques to run our developed app on the remote server to help doctors in the suburban area. Two other chest-related diseases: secondary pulmonary tuberculosis and community-acquired pneumonia, will be covered in this talk.
讲者简介：Yudong Zhang is a professor at the School of Computing and Mathematical Sciences, University of Leicester, UK. His research interests include deep learning and medical image analysis. He is the Fellow of IET, Fellow of EAI, and Fellow of BCS. He is the Senior Member of IEEE, IES, and ACM. He is the Distinguished Speaker of ACM. He was the 2019 & 2021 recipient of Clarivate Highly Cited Researcher. He has (co)authored over 400 peer-reviewed articles. There are more than 50 ESI Highly Cited Papers and 5 ESI Hot Papers in his (co)authored publications. His citation reached 22817 in Google Scholar (h-index 84). He has conducted many successful industrial projects and academic grants from NIH, Royal Society, GCRF, EPSRC, MRC, Hope, British Council, and NSFC. He has served as (Co-)Chair for more than 60 international conferences and workshops (including more than 10 IEEE or ACM conferences). More than 50 news presses have reported his research outputs, such as Reuters, BBC, Telegraph, Physics World, UK Today News, etc.
