Grant: Research Tools and Instruments - Category 1 (<$150,000)

The applicant, Nick Cercone, moved to York in September 2006 as Dean of Science & Engineering. The computing environment he built at Dalhousie was needed and left behind. Currently Cercone supervises1 full time post-doc, 1 part-time post-doc, and 8 graduate students (6 Ph.D. students and 2 M.Sc. students). Two talented York faculty, Aijun An (data mining, machine learning) and Jimmy Huang (information retrieval) join this proposal; they supervise a dozen students. As faculty members with related interests and critical need for equipment, the three will share/maintain their research computing environment. This group supervises current students in several projects, notably "Finding best evidence for evidence-based best practice recommendations in health care" and "Ultra-Large scale systems (ULS) with application in evidence based medicine (EBM)". For example, the goal of the second project is to develop and manage ULS, our role is to develop methods and advanced tools to help doctors/patients find relevant information, discover interesting medical database patterns from and obtain recommendations for cost-effective treatments. A primary long-term goal of this research is to develop a decision support system for EBM management, quality control and best practice recommendations for health applications. Research results will improve access, management and manipulation of information in a networked environment by: (1) building prototypes for adaptive information extraction, text/data mining from (online) documents to find evidence on which to base best practice recommendations; and (2) employ machine learning techniques, e.g., multiply sectioned Bayesian networks, to infer probabilistic interpretations to validate evidence. This equipment will support this group's research, and their students and post-docs.