Chris McIntosh is a Computer Scientist, trained in Computer Vision and AI in medicine. He is the recipient of academic awards from NSERC, CIHR, and the Michael Smith Foundation for Health Research. His PhD dissertation developed AI-driven methods for quantitative medical image analysis through manifold learning, and received an honourable mention for the top dissertation in computer vision and medical image analysis by the Canadian Image Processing and Pattern Recognition Society. His research focuses on the theory and clinical application of AI in medicine for improving patient care including transfer learning, meta learning, computer vision, and explainable AI. Applications include deep learning for automated diagnosis, segmentation, quality assurance, and treatment planning. His past work on AI in radiation therapy has been approved for clinical use by regulatory bodies, commercialized, and deployed in hospitals around the world, using AI to deliver reproducible, high quality cancer care.
Week 6 Speaker: A Machine Learning Radiation Therapy System from Bench to Bedside (Nature Medicine, June Issue, 2021)
We describe an AI model that generates radiation treatment plans for prostate cancer patients. AI was successfully deployed in a standard-of-care clinical setting, providing gains in efficiency, improved treatment quality, and an understanding of physicians’ decision-making and perceptions of AI use when patient care is at stake.