COVID-19 is a pandemic disease that caused more than 6.59 million deaths as of 30th October 2022.
A CT scan is a medical imaging technique used in radiology to get detailed images of the body non-invasively for diagnostic purposes. Traditional manual labelling of CT-based scans is tedious. To solve the problem, our laboratory employs intelligent automation methods, such as transfer learning, graph neural networks, attention neural networks and weakly supervised networks. We also use cloud computing techniques to run our developed app on the remote server to help doctors in suburban areas.
Two other chest-related diseases; secondary pulmonary tuberculosis and community-acquired pneumonia will be also be covered in this lecture.
About the Speaker
Prof 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 a Fellow of IET, Fellow of EAI, and Fellow of BCS. He is a Senior Member of IEEE, IES, and ACM where he is a Distinguished Speaker.
Prof Zhang was the 2019 & 2021 recipient of Highly Cited Researcher award by Clarivate. 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 22641 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. More than 50 news outlets have reported his research outputs, such as Reuters, BBC, Daily Telegraph, Physics World and UK Today News.