Past Events From 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".

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.)

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 

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.

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.

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. 

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.

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.

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. 

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.

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. 

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.

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. 

Dr. Bo Wang is a tenure-track assistant professor of the Department of Laboratory Medicine and Pathobiology and the 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.

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.

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.

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.