2018 Webinar Artificial Intelligence. The voice of reason, and the science of reason.
Dr. Mitsouras received his Ph.D. in computer science at MIT in 2004 and since then he has been a faculty member at the Department of Radiology at Brigham And Women’s Hospital and Harvard Medical School, and at the University of Ottawa since 2017. Dr. Mitsouras has developed a number technologies in CT and MR imaging and introduced them into clinical practice, including a component of the 3D SPACE MRI sequence now used to perform high resolution 3D imaging throughout the body, the discovery of flow information embedded in arterial contrast enhancement patterns in CT angiography which has led to improved techniques to assess the hemodynamic significance of coronary artery disease using computational fluid dynamics (CT-FFR), and the introduction of 3D printing technologies for patient-specific precision surgery. He has published >75 peer-reviewed articles, 6 book chapters, and has been awarded >$1M USD of extramural funding from the U.S. National Institutes of Health, the American Heart Association, and commercial entities in support of his research
A list of Dr. Miitsouras' publications can be found here: https://scholar.google.com/citations?user=WVGPzTQAAAAJ&hl=en
Dr. Leonid Chepelev is currently a radiology resident physician at the University of Ottawa. He hails from a background in computational chemistry and bioinformatics. As part of his doctoral studies at Carleton University and the European Bioinformatics Institute, he has been responsible for automated computational resource integration, ontology development, and human-accessible machine learning. His current interests include the extension of clinical applications of radiology, including through 3D printing and artificial intelligence.
Frank J. Rybicki, MD, PhD, is Professor and Chair of Radiology at the University of Ottawa and The Ottawa Hospital. Dr Rybicki is the Medical Director for Imagia, a leader in artificial intelligence. He is also Chair of the American College of Radiology Appropriateness Criteria®. In 2007, Dr. Rybicki introduced wide-area detector CT to radiology. He also made the initial observation that contrast hemodynamics are related to blood flow. Both of these technology is now globally used for patient care and research. Dr. Rybicki pioneered medical 3D printing in healthcare; he is the Editor-in-Chief of 3D Printing in Medicine and in 2014 he founded and was the first Chairperson of the Radiological Society of North America Special Interest Group on 3D printing.
Clinical Interests: Cardiovascular computed tomography and magnetic resonance
Residency: Brigham and Women’s Hospital, Harvard Medical School
Nicolas Chapados holds an engineering degree from McGill University and a PhD in Computer Science from University of Montreal, Canada. While still writing his thesis and jointly with his advisor Yoshua Bengio, he co-founded ApSTAT Technologies in 2001, a machine learning technology transfer firm, to apply cutting-edge academic research ideas to areas such as insurance risk evaluation, supply chain planning, business forecasting, and hedge fund management. He also co-founded two spin-off companies: Imagia, to provide AI-based actionable predictive oncology analytics atop medical imaging data, and Chapados Couture Capital, a Quebec-registered quantitative asset manager. Previously, Nicolas was a member of the speech recognition research group at Nortel Networks, where he led the research and implementation of a natural-language dialog manager for continuous speech recognition applications. He holds the Chartered Financial Analyst (CFA) designation.
Dr. Kafi is presently the Director of Clinical Strategy and Oncology at Imagia. He did his graduate studies at UCLA's Johnson Comprehensive Cancer Center where his research focused on development and translation of targeted immunotherapies, cancer vaccines and immunomodulation strategies in hematologic malignancies. He later studied medicine and Radiation Oncology at McGill University after which he focused his time on development or Artificial Intelligence in healthcare.
Dr. Tang is presently an Assistant Professor for the Department of Radiology at Université de Montréal. His specialty includes magnetic resonance imaging, computed tomography and ultrasound of abdominal and pelvic organs. He completed his doctorate in Medicine at the University of Sherbrooke in 2000. After completing his specialty degree in Radiology at the University of Montreal in 2005, he attended the University of Toronto to complete fellowship training in Abdominal Imaging in 2006. In September 2006, Dr Tang joined the team of radiologists at the CHUM and Varad Radiology Clinic. His research includes non-invasive imaging-based strategies for diagnosis and monitoring of chronic liver disease. Dr. Tang is supported by prestigious awards from the Fulbright Program and the Canadian Institutes of Health Research, he pursued a research fellowship in liver magnetic resonance imaging at the University of California, San Diego in 2012. In 2015 he received the CAR Young Investigator Award.
Dr. Chong is an Assistant Professor for the Department of Radiology at McGill University. He completed radiology residency training at McGill University and an Abdominal Imaging fellowship at Yale New-Haven Hospital. His clinical interests include abdominal and GU/Prostate MR imaging with research interests in the application of natural language process for medical imaging appropriate utilisation and the application of Radiomics/Deep Learning for oncologic prognostic modelling and Augmented Radiology.
Dr Thornhill completed her M.Sc. and Ph.D. in Medical Biophysics from the University of Western Ontario, where her work focused on cardiac magnetic resonance imaging (MRI). She continued on to do postdoctoral research fellowships at McMaster University and the University of Toronto (Hospital for Sick Children). Since 2010, Dr Thornhill has been working as an Imaging Scientist in the Department of Medical Imaging at The Ottawa Hospital, with special interests in cardiac MRI as well as quantitative pattern analysis of medical images. She is also an adjunct research professor in the Department of Systems and Computer Engineering at Carleton University.