IEEE 33rd International Symposium on
Computer Based Medical Systems (CBMS)

Mayo Clinic, Rochester, MN
June 22 - 24 July 28 - 30, 2020
Important note: The committee moves CBMS 2020 symposium "ONLINE" due to COVID-19 events.

Conference program

Program (Time zone: GMT-4:00)
    July 28 (Day 1): complete program with zoom link (plus session chairs) info., click ''PDF''.
    July 29 (Day 2): complete program with zoom link (plus session chairs) info., click ''PDF''.
    July 30 (Day 3): complete program with zoom link (plus session chairs) info., click ''PDF''.
    Presentation guidelines (strict) for authors: ''PDF''
    Deadline: July 24, 2020

Important note: If you find any issues, please contact us as soon as you can.

Time zone for conference program is set to GMT-4:00. Click to know what time is it now?

Zoom links:
Zoom links are provided to (registered)authors, session chairs, and speakers via email. Check your email with the subject ''CBMS2020: Zoom Links and Sessions''. Check your program (day 1 to day 3) and get connected by clicking the right zoom link.

Click the following document, CBMS2020: Zoom Links and Sessions (passkey protected). You will receive an email for a passkey.

Keynote speakers

    Daniela Stan Raicu
    Associate Provost for Research & Professor of School of Computing
    College of Computing and Digital Media
    DePaul University, Chicago.

Title of the talk: Deep Learning for Explainable Computer-Aided Diagnosis. download (talk).

Daniela S. Raicu is an Associate Provost for Research and a Professor of School of Computing, College of Computing and Digital Media at DePaul University, Chicago. She is the co-director of the Medical Informatics and the Intelligent Multimedia Processing Laboratories. Daniela is also the Director of the Data Mining and Predictive Analytics Center at DePaul. Her research interests include biomedical and health informatics, medical imaging, computer vision, data mining and machine learning. She has authored more than 150 journal and conference papers in these areas. Daniela's projects have been funded by the National Science Foundation (NSF), Argonne National Laboratory, Department of Education, and MacArthur Foundation. She is the recipient of the DePaul Excellence in Teaching Award in 2008, the DePaul Spirit of Inquiry Award in 2010, the IBM Faculty Innovation Award in 2010, and the St. Louise de Marillac Women of Spirit & Action Award in 2016. She also serves on the National Executive Council of the Upsilon Pi Epsilon (UPE) honor society in Computer and Information Sciences since 2008. Daniela holds a Ph.D. in Computer Science from Oakland University, Michigan, a M.A. in Computer Science from Wayne State University, Michigan, and a B.S. in Mathematics from University of Bucharest, Romania.

    Linlin Shen
    Professor, College of Computer Science and Software Engineering
    Director of Computer Vision Institute
    Shenzhen University, China

Title of the talk: Deep learning based medical image analysis: problems and solutions.

Prof. Linlin Shen is currently a “Pengcheng Scholar” Distinguished Professor at Computer Science and Software Engineering, Shenzhen University, Shenzhen, China. He is also an Honorary professor at School of Computer Science, University of Nottingham, UK and a Consultant on computer vision for Huawei Technology Co. Ltd. He serves as the director of Computer Vision Institute, AI aided Medical Image Analysis & Diagnosis and China-UK joint research lab for visual information processing. He also serves as the Co-Editor-in-Chief of the IET journal of Cognitive Computation and Systems. He received the BSc and MEng degrees from Shanghai JiaoTong University, Shanghai, China, and the Ph.D. degree from the University of Nottingham, Nottingham, U.K. He was a Research Fellow with the University of Nottingham, working on MRI brain image processing. His research interests include deep learning, facial analysis and medical image processing. Prof. Shen is listed as the Most Cited Chinese Researcher by Elsevier. He received the Most Cited Paper Award from the journal of Image and Vision Computing. His cell classification algorithms were the winners of the International Contest on Pattern Recognition Techniques for Indirect Immunofluorescence Images held by ICIP 2013 and ICPR 2016.

    Bradley J Erickson
    Consultant & Professor of Radiology
    Department of Radiology
    Mayo Clinic, Rochester, MN

Title of the talk: How AI will affect the practice of Medicine.

Bradley J Erickson, MD PhD, received his MD and PhD degrees from Mayo Clinic. He went on to be trained in radiology, and then a Neuroradiology fellowship at Mayo, and has been on staff at Mayo since that time, where he does clinical Neuroradiology, has been chair of the Radiology Informatics Division and Associate Chair for Research. He has been awarded multiple external grants, including NIH grants on MS, brain tumors, polycystic kidney disease, and medical image exchange. He is a former president of the Society of Imaging Informatics in Medicine, is current Chair of the American Board of Imaging Informatics, and serves on the Board of the IHE USA. He recently won the nVIDIA Global Impact Award for his work on deep learning applications in medical images. He now is scientific director for AI at Mayo, and also Chairs NCI's Image Data Commons, which is a public resource of image data for advancing science.

Mayo Clinic, Minnesota - Rochester
200 First St. SW
Rochester, MN 55905

COVID-19 paper: AI-driven tools for coronavirus outbreak.