Advancing precision healthcare
As a distinguished medical professional at the forefront of integrating artificial intelligence (AI) into healthcare, Ross has significantly advanced precision medicine, through groundbreaking applications of machine learning and deep learning in medical imaging and cancer treatment for over 30 years.
Ross is an Amii Fellow, Canada CIFAR AI Chair, a professor in the Department of Medicine and the Senior Program Director of Artificial Intelligence Adoption with Alberta Health Services.
From 2019 to 2021, Ross was the inaugural Artificial Intelligence Officer at the H. Lee Moffitt Cancer Center and Research Institute in Tampa, Florida. 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.
As a professor and the inaugural director of the Department of Radiology at the Mayo Clinic in Arizona (2011 to 2019), Ross established the Division of Medical Imaging Informatics, an interdisciplinary team of scientists and student collaborators to advance medical imaging informatics and AI applications in healthcare.
He also spearheaded the deployment of mobile imaging technology, enhancing precision health by providing clinicians with rapid, secure access to medical images and reports. This initiative's success led to the adoption of enterprise-wide mobile image-viewing solutions.
From 2017 to 2019, Ross spearheaded a global effort to create a groundbreaking deep-learning system for analyzing MRI scans of brain cancer patients. This advanced system capable of processing scans in just 1-2 minutes, was rated by neuroradiologists as outperforming human technicians in a randomized, blinded comparison.
Before that, 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.
Areas of
Expertise
Artificial Intelligence
Biomedical imaging
Machine Learning & Deep Learning
Federated learning
Telemedicine
Time-frequency analysis
Precision Health & Oncology
Natural Language Processing
Neural Networks
Highlights
$1M in funding for “Jenkins”
In 2024, Ross and his research team received $1M in funding for “Jenkins”, a revolutionary AI-scribe tool that directly addresses the growing demands of emergency departments.
Paper named one of Nature’s Top 25
Ross’ paper “Federated Learning Enables Big Data for Rare Cancer Boundary Detection” was named one of Nature’s Top 25 Health Sciences Articles and one of the most downloaded papers in 2023.
