The field of machine learning provides tools and technologies for finding significant patterns in data, such as the correlations between the results of clinical tests and treatment success. It is most appropriate in information processing situations where training data (such as a database of case studies) is available and it is difficult (or not cost effective) to "engineer in" the solution.
Machine learning is a proven technology that has had significant impact on both industry and science. There are numerous successful applications of machine learning related to health information, the oil industry, gene identification and chemical process control, to name a few.
This group has close ties to the areas of many related areas, including bioinformatics, database and data mining, and vision and robotics. Graduate students may be interested in a graduate specialization in Statistical Machine Learning (a joint program with Mathematics and Statistical Sciences).
- Alberta Innovates Centre for Machine Learning
- Medical Informatics: We are involved with a wide range of projects, in collaboration with many teams of medical researchers/clinicians, to produce systems that effectively learn classifiers that make accurate predictions about future patients. We are now dealing with various cancers (breast, brain, leukemia), transplant, diabetes, stroke, and depression.
- Brain Tumor Analysis Project: A collaboration between the University of Alberta's Computing Science Department and Cross Cancer Institute to apply machine learning and computer vision techniques to the analysis of brain tumour patient MRI data.