Artificial Intelligence in Pathology – The Future is NOW…ish
Wednesday, June 19th, 2024 at 12pm ET
Speakers
Eric Chen MD, PhD
Rochester, Minnesota, USA
Consultant Pathologist and Associate Professor
Department of Laboratory Medicine and Pathology
Mayo Clinic
Dr. Chen is a consultant and associate professor of pathology and laboratory medicine at Mayo Clinic, Rochester, MN. His clinical specialty interest is in pathological diagnosis of GI, pancreas and liver diseases and clinical application of immunohistochemistry in cancer diagnosis and predicative biomarker evaluation using artificial intelligence (AI) algorithms. He currently serves as the vice chair of anatomic pathology division biomarker utilization, associate director of biomarker imaging analysis lab and associate director of GI pathology resident/fellowship training program.
Dr. Chen received his medical degree from Zhejiang University School of Medicine in China followed by PhD in microbiology and immunology from University of Minnesota. His AP/CP residency and surgical pathology fellowship training was from Washington University in St. Louis. He also completed GI and liver pathology fellowship training at Johns Hopkins Medical Institutions.
Dr. Chen is academically active with more than 120 peer reviewed articles, published abstracts, book chapters and co-edited two textbooks in diagnostic application of immunohistochemistry and GI pathology, respectively. He serves in several national and international organizations including CAP IHC committee member, USCAP resident advisory subcommittee member, past-chair of pathology committee of international liver transplant society (ILTS) and board member of international quality network of pathology (IQNPath). He is one of the GI section editors for Archive of Pathology &Laboratory Medicine.
Alireza Sadeghian PhD
Toronto, Ontario
Professor, Department of Computer Science, Faculty of Science, Toronto Metropolitan University
Chair, IEEE Signals & Computational Intelligence Chapter, Toronto Section
Affiliate Scientist, Li Ka Shing Knowledge Institute, Keenan Research Centre, St. Michael’s Hospital
Founding Director, Advanced Artificial Intelligence Lab (AI2)
Dr. Alireza Sadeghian has been with the Department of Computer Science at Toronto Metropolitan University since 1999, where he holds the position of the Professor, and was the Founding Chair of the Department of Computer Science from 2005 to 2015. Dr. Sadeghian has extensive expertise in the areas of Artificial Intelligence, Machine Learning, Deep Learning, and modeling of complex dynamical systems particularly related to medical and industrial applications. He is also the founding Director of the Advanced Artificial Intelligence Lab (AI)2, Computational Intelligence Initiative (CI2) and Ubiquitous and Pervasive Computing Laboratories (UPCL). Dr. Sadeghian has supervised and trained 12 postdoctoral fellows, 13 PhD, and 31 Master’s students, as well as 68 research assistants. He has published over 175 journal manuscripts, refereed conference papers, and book chapters, as well as 2 edited books, 2 invention disclosures, and 2 patents.
Dr. Sadeghian is the recipient of various awards and recognitions including TMU Dean’s Research Award, TMU Outstanding Contribution to Graduate Education Award, TMU Teaching Excellence Award, TMU Distinguished Service Award, Royal Canadian Institute for the Advancement of Science Top 25 Canadian Scientists, IEEE Toronto Outstanding Leadership Award, St. Michael’s Hospital Foundation, People’s Choice Award, and Innovative Health Award — runner-up — Angels Den Competition, St. Michael’s Hospital Foundation.
Dr. Sadeghian has been actively involved with a number of international professional and academic boards. His past activities include IEEE Education Activity Board; Chair of IEEE Toronto Section, Technical Society Chapter, Magnetics; and NAFIPS Board (North American Fuzzy Information Processing Society). Presently, he is the Vice-Chair of the IEEE Computational Intelligence, Standards Committee, Chair of IEEE Computational Intelligence Technical Society Chapter, Toronto Section, a member of the IEEE Standard Associations – Standards Development for the Computational Intelligence Society Standards Committee, XAI – eXplainable AI Working Group, IEEE P2976 Working Group.
Dr. Sadeghian is also on the Editorial Board of Applied Soft Computing Journal and serves as an Associate Editor of IEEE Access, Information Sciences, and Expert Systems Journal. He has served on over 80 conferences as Honorary Chair/General Chair/Organizer/Technical/Track Program Committee member, and has been a reviewer of many granting bodies including NSERC, MITACS, OCE, CFI, PRECARN, and PREA.
Learning Objectives
After this episode, the participant will be able to:
1. Define key concepts and terms of artificial intelligence (AI) including image analysis, linear regression, machine learning, deep learning, neural network and how they relate to pathology.
2. Describe 3 current or emerging applications of AI in pathology in the areas of assisted diagnostics, biomarker readout, prognostication, or discovery.