These previous events were either hosted by T-CAIREM or featured members of our leadership team.
December 12, 2022
In the final Trainee Rounds seminar for 2022, Dr. Sun-Ho Lee presented his research entitled: "Machine learning-based microbiome risk model predicts future development of Crohn’s disease among healthy first-degree relatives".
September 20, 2022
In this panel discussion, three experts discussed their experiences commercializing their AI research in the healthcare field. Featured panellists included:
• Dr. Igor Jurisica (Senior Scientist at Krembil Research Institute, UofT Professor, Visiting Scientist at IBM CAS)
• Dr. Matthew Platt (Associate Director, CDL-Toronto, Rotman School of Management, University of Toronto)
• Prof. Mara Lederman (Co-founder and Chief Operating Officer, Signal 1 AI Inc.)
September 8, 2022
T-CAIREM hosted an information session for AI in medicine researchers interested in applying for two grants we're offering in 2022 for $100,000 each:
• Temerty Innovation Grant for AI in Medicine
• Family Medicine (FAFM & CFPC) - Temerty Innovation Grant
July 26, 2022
Due to overwhelming interest in the 2022 Vector Institute-Temerty Clinical AI Integration Grant, we held an information session in July 2022. If you’re thinking of applying, this video may answer some of your questions.
July 18, 2022
For the July 2022 Trainee Rounds, our two presenters explained their research in vascular surgery. Dr. Ben Li presented his work using machine learning in vascular surgery while researcher Nitish Bhatt discussed his work using deep convolutional neural networks to automate detection of plaques in carotid ultrasound.
June 28, 2022
Dr. Mojgan Hodaie, a professor with the Department of Surgery and Institute of Medical Science, explained her research into understanding pain using artificial intelligence. In this Temerty Centre Speaker Series presentation, she shared the body of work that points to objective measures drawn from advanced brain imaging, and how AI is helping shape the future of pain research.
June 27, 2022
This 2022 Trainee Rounds featured Zienab Navidi explaining her research into using machine learning to identify predictors of heart transplant survival. Researcher Bonnie Chao discussed her work into computer-guided radiographic evaluation of human donor lungs.
June 13, 2022
The latest installment of the T-CAIREM's 2022 Trainee Rounds featured Brianne Laverty discussing a machine-learning model that used tumour whole genome sequencing data to identify individuals with Li-Fraumeni syndrome. Physician Dr. Christopher Noel explained his research to develop and validate a machine learning algorithm for emergency department use and unplanned hospitalization in patients with head and neck cancer.
June 3, 2022
Dr. Amol Verma discussed how Canada could harness the potential of AI in medicine for the future. He addressed key challenges and strengths of AI in medicine in Canada and discussed GEMINI and its efforts to create large, granular, high-quality datasets. He also explained his work with CHARTwatch and the process of implementing an AI-based early warning system in a hospital.
May 30, 2022
The first session T-CAIREM's 2022 Trainee Rounds included Brokoslaw Laschowski discussing the development of wearable computer vision systems powered by deep learning for automated control and decision making of robotic leg prostheses and exoskeletons. Researcher Michael Lee explained his work developing a compound computational pathology workflow for automated and integrated analyses of morphologic and molecular histopathological features.
May 16, 2022
Dr. Brian Courtney is an interventional cardiologist at Sunnybrook Health Sciences Center in the Schulich Heart Program. He is an inventor on over 25 U.S. patents and co-author on over 25 published manuscripts. In this special lecture for T-CAIREM, he describes his personal experiences developing new medical technologies, as well as some of the challenges and opportunities in med-tech commercialization in Canada.
May 10, 2022
Dr. Mamatha Bhat is a staff hepatologist and clinician-scientist in the Ajmera Transplant Centre at the University Health Network, Assistant Professor at University of Toronto's Division of Gastroenterology & Hepatology, Department of Medicine, and Director of the Clinician-Scientist Training Program for the Department of Medicine. In this guest lecture, she discusses her research using machine learning to address critical clinical challenges in liver transplantation and provides specific examples where it can be used to optimize outcomes and equity.
April 19, 2022
Dr. Devin Singh is a practicing Paediatric Emergency Medicine Physician at SickKids. His research focuses on the use of machine learning to solve some of healthcare’s largest problems. Most recently he founded Hero AI, an innovative start-up lab dedicated to empowering patients and healthcare providers with AI. In this guest lecture, he discusses opportunities for the use and translation of machine learning models into common emergency department workflows and how AI can enable clinicians to move from decision support to true clinical automation.
March 22, 2022
Dr. Bo Wang is tenure-track assistant professor of Department of Laboratory Medicine and Pathobiology and Department of Computer Science at the University of Toronto. He holds a CIFAR AI Chair at the Vector Institute and is the Temerty Professor in AI Research and Education in Medicine with T-CAIREM. He also leads the AI team for the Peter Munk Cardiac Centre at the University Health Network. In this guest lecture he discusses the opportunities and challenges of implementing artificial intelligence for organ transplantation.
February 22, 2022
Dr. Stephen Friend is an authority in the fields of genetic resilience, cancer biology, and digital health. He is now a co-founder and President of 4YouandMe, the Founder and Chairman of Sage Bionetworks, and based at Oxford University as a Visiting Professor of Connected Medicine. In this guest lecture, he discusses how digital devices might allow us to follow symptom transitions and the effects of the fabric of life on chronic conditions.
January 28, 2022
To help launch the 2022 T-CAIREM Summer Student Research Program, open to all undergraduate or medical students at a Canadian university, T-CAIREM held this information session on January 28, 2022. We hope this recording helps answer questions from potential applicants about the paid AI in medicine summer research positions.
January 11, 2022
AI applications across a wide range of specialties are beginning to transition from research papers into impact at the point of care. Deploying AI successfully and responsibly involves considering the technical and sociological impacts these tools will have in the clinical environment. Drs. Adedinsewo, Berlin, and Liu have developed and are working to deploy algorithms across cardiology, radiation oncology, and critical care.
December 7, 2021
In this final installment of the 2021 Trainee Rounds seminars, Anton Nikouline (Resident Physician PGY5, Department of Medicine, Division of Emergency Medicine, University of Toronto) explained his research "Machine Learning in the Prediction of Massive Transfusion in Trauma." Tara Upshaw (Graduate, Institute of Medical Science (2020), University of Toronto; Medical student, University of Calgary) discussed her research "Priority applications, opportunities and challenges for artificial intelligence in primary care: Results of a national deliberative dialogue."
November 9, 2021
In this Temerty Centre Speaker Series lecture, Harvard University computer science professor Dr. Finale Doshi-Velez discussed the applications of reinforcement learning in healthcare.
October 5, 2021
In the October Trainee Rounds seminars, Navpreet Kamboj (PhD Student, Lawrence S. Bloomberg Faculty of Nursing) discussed her research into developing a nitroglycerin dose titration decision support system. Ryan Daniel (Medical Student, Temerty Faculty of Medicine) explained machine learning-based innovation in ocular pediatric assessment using point of care ultrasound.
September 28, 2021
Dr. Rahul G. Krishnan is an Assistant Professor of Computer Science and Medicine (Laboratory Medicine and Pathobiology) at the University of Toronto and a member of the Vector Institute where he holds a CIFAR AI Chair. In this talk he discusses some of the recent advances in the use of tools in machine learning to tackle challenges that arise in the management and care of chronic diseases (with a focus on precision oncology).
August 10, 2021
In August 2021, the T-CAIREM 2021 Student Trainee Rounds featured outstanding work from emerging University of Toronto researchers. Anastasia Razdaibiedina (PhD student, Computational Biology and Machine Learning, University of Toronto) presented on her research "Discovering gene-disease relationships with deep learning" and Michael Balas (Medical student, Temerty Faculty of Medicine, University of Toronto) discussed "Using Artificial Intelligence to Identify Intracranial Hemorrhage and Predict Patient Outcomes".
June 1, 2021
The T-CAIREM 2021 Student Trainee Rounds showcases outstanding work from emerging University of Toronto researchers who are exploring new ways to incorporate Artificial Intelligence (AI) into healthcare. In this public presentation Anglin Dent (MSc candidate, Department of Laboratory Medicine & Pathobiology) discussed "Development and Potential Applications of Unsupervised DigitalPathology Tools in the Resolution of Tumor Heterogeneity." Dr. Jethro Kwong (Division of Urology, Department of Surgery) discussed "Development and external validation of an explainable machine learning model to predict risk of side-specific extraprostatic extension in men with prostate cancer."
May 11, 2021
T-CAIREM hosted data scientist Dr. Jenna Wiens, associate professor of computer science and engineering and co-director of Precision Health at the University of Michigan (Ann Arbor). Dr. Wiens' primary research interests lie at the intersection of machine learning, data mining, and healthcare. As part of the Temerty Centre Speaker Series, Dr. Wiens discussed how Artificial Intelligence (AI) could augment clinical decision making
April 13, 2021
The T-CAIREM 2021 Student Trainee Rounds is a competitive seminar series that highlights innovative and outstanding research at the intersection of artificial intelligence (AI) and healthcare across the University of Toronto’s graduate and professional programs. In this first presentation Tahera Yesmin (PhD candidate, Department of Mechanical and Industrial Engineering) presented "A machine learning approach to predict the number of beds that will require cleaning and staff requirements in the emergency department". Sujay Nagaraj (MD/PhD candidate, Department of Computer Science and Temerty Faculty of Medicine) discussed his work on the "Development and implementation of a machine learning tool to automate vascular catheter access detection in a pediatric critical care unit."
March 2, 2021
In this public lecture hosted by T-CAIREM, Dr. Leo Anthony Celi—MIT data scientist and medical doctor—discusses the current gaps in medical knowledge stemming from the systematic exclusion of people from health research. These gaps negatively impact health outcomes for everyone, but especially those in groups typically under-represented in health research. Recent developments in machine learning and AI technologies hold promise to address these issues and help create a future that benefits all.
January 19, 2021
Dr. Eric Topol — one of the top ten most cited researchers in medicine — joined T-CAIREM Director, Professor Muhammad Mamdani, to discuss the future of AI in medicine. Dr. Topol is the Founder and Director of the Scripps Research Translational Institute and a professor of Molecular Medicine and Executive Vice-President of Scripps Research.
December 9, 2020
"How will Artificial Intelligence affect the delivery of healthcare?" was the title of this online discussion among Dr. Bo Wang, T-CAIREM Education Lead Dr. Laura Rosella, and T-CAIREM Director Dr. Muhammad Mamdani. Moderated by Dr. Rahul Gopal Krishnan, the panel discussed ethics, safety, training, and AI’s influence on decision-making in healthcare.
November 10, 2020