Julia Patriarche, Ph.D.
Department of Information and Computer Sciences
Application of Computers to Medicine
I did my undergraduate degree at Queen’s University in
My work is situated at the cross-roads of a number of fields. My current primary focus is image and signal processing algorithms applied to clinical medical image analysis. My work, being fundamentally interdisciplinary, requires that I have an understanding of artificial intelligence (machine learning, machine vision, optimization), human vision, human perception, image processing, pattern analysis, mathematical modeling, software engineering, magnetic resonance imaging, oncology, neurology, radiology, and other fields. My focus also requires that I be a medical scientist – that is, that I be able to use sound scientific methodology: 1) to demonstrate the efficacy of the systems which I develop, and 2) to use them to make medical discoveries.
The lion’s share of my research time is focused on the development of a system for the detection of change in serial magnetic resonance imaging studies of brain tumor patients. The system is a multi-level AI system, which is a proof of principle, of how such systems can augment patient care, by doing routine tasks better than a human can do them (in theory – but we have evidence to support this assertion), and by elevating the role of the clinician to the more interesting and less routine parts of patient care. In addition to its theoretical value, the system is a working prototype, and is currently being used in patient care at Mayo Clinic. We recently won “Best Paper of 2007” from Society for Imaging Informatics in Medicine (SIIM) for one of the papers associated with this work.
People have a fundamental desire to improve the quality and length of their lives. Computers are going to be instrumental in leading to such improvements, for the foreseeable future, and there are many fascinating aspects of how this is going to happen. I share the opinion that the people who are alive today, have a very good chance of benefiting from technologically enabled radical life extension. People who are studying computers, today, have an opportunity to be the movers behind these changes.