Past Events From 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."

In this Temerty Centre Speaker Series lecture, Harvard University computer science professor Dr. Finale Doshi-Velez discussed the applications of reinforcement learning in healthcare. 

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.

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). 

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".

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."

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

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."

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 underrepresented 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.

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.