CIFAR Canada AI Chair
Fellow, Alberta Machine Intelligence Institute
Alberta Health Services Chair in Artificial Intelligence in Health
Professor, Department of Medicine, Faculty of Medicine & Dentistry,
Adjunct Professor, Department of Computer Science, Faculty of Science, University of Alberta
Edmonton, Alberta Canada
January 15, 2025
Accomplished professional with 30-year history of success building interdisciplinary teams for research and delivering innovative solutions in AI, Machine Learning and Deep Learning for Precision Healthcare.
Dr. Mitchell is a Canada CIFAR AI Chair, the Alberta Health Services (AHS) Chair in AI in Health, a professor in the Department of Medicine, and an adjunct professor in the Department of Computer Science at the University of Alberta. He is also a fellow with the Alberta Machine Intelligence Institute.
Dr. Mitchell was the inaugural artificial intelligence officer at the H. Lee Moffitt Cancer Center and Research Institute in Tampa, Florida from 2019 to 2021. There he led efforts to develop AI tools to improve the efficiency and quality of cancer care, including models to predict patient outcomes from electronic health record data, and natural language processing to infer diagnostic codes from free-text pathology reports. He was a professor and the inaugural director of the Division of Medical Imaging Informatics in the Department of Radiology, Mayo Clinic in Arizona, from 2011 to 2019. He was a professor of Biomedical Engineering, Radiology, and Clinical Neurosciences at the University of Calgary from 2000 to 2011. He received his PhD at the University of Western Ontario and has been working in the fields of biomedical imaging, artificial intelligence, and machine learning in healthcare for 30 years.
Dr. Ross Mitchell speaking to the Insitute of Health Economics about AI and precision health research and the future of medicine.
AI researcher and AMII fellow Ross Mitchell has created a large language model that uses artificial intelligence to ease the daily workload of Alberta physicians and make the health-care system more efficient. Emily Mertz explains
Can artificial intelligence be used to find innovative ways to improve our healthcare system? Professor Ross Mitchell believes so. He’s the Alberta Health Services “Chair in A.I. in Health” and he joins to explain how the technology can effectively be used to drive healthcare innovation in our Province.
"The Canadian Institute for Advanced Research (CIFAR) and Canada’s three National AI Institutes today announced the appointment of eight outstanding researchers as Canada CIFAR AI Chairs, as well as the first cohort of Chairs to be renewed under the second phase of the Pan-Canadian AI Strategy at CIFAR. The appointments bring the number of Canada-CIFAR AI Chairs to 126, continuing to grow Canada’s robust AI research ecosystem and advancing Canada’s global leadership in AI."
This paper describes a large study involving 71 hospitals across 6 continents to improve the identification and outlining of glioblastoma brain tumors. Delineating these tumors is the first step in treatment planning. However, it is very difficult since these are diffuse infiltrative lesions. Furthermore, since this deadly disease is quite rare, it has been difficult to collect enough patient data to train a deep neural network to perform this task with high accuracy. Our study used federated learning (move-the-algorithm-to-the-data) to allow us to analyze scans from over 6,300 patients worldwide. The size and diversity of this dataset allowed us to achieve a 33% delineation improvement for surgically targetable tumor over a benchmark deep learning system.
I edited the Frontiers Research Topic "Computational Radiomics for Cancer Characterization". This is a free collection of 36 peer reviewed manuscripts. Together, they describe new methods to characterize, diagnose, treat and monitor cancer using sophisticated machine learning algorithms. These algorithms learn to identify patterns in medical images that help predict patient outcomes.
This patent describes methods to predict the spatial distribution and genetic variability of brain tumors based on machine learning of multi-contrast MRI exams. This information could help physicians target tissue for therapy, select treatment types, then monitor the response to therapy.
The Chancellor's Forum is an initiative of the University of Alberta Senate that invites the public to campus to engage with a timely topic related to the University of Alberta. Senators assist with the planning of the Chancellor's Forum and engage Faculties and other campus units with expertise in the selected topic.
Dr. Joseph Ross Mitchell believes Alberta-based AI may accelerate the health-care process
BY KATRINA TURCHIN | MAY 4, 2022
The aim of this study is to develop a Transformer-based system to automatically extract detailed tumor site and histology information from free-text oncological pathology reports.