HONG KONG BAPTIST UNIVERSITY
FACULTY OF SCIENCE

Department of Computer Science Colloquium
2008 Series

Finding best evidence for evidence-based best practice recommendations in health care

Prof. Nick Cercone
Dean and Professor of Computer Science
York University
Canada

Date: May 30, 2008 (Friday)
Time: 11:00 am - 12:00 pm
Venue: OEE601, Oen Hall (East Wing), Ho Sin Hang Campus

Abstract
Medications are not always effectively used and misuse may harm patients. Drugs are the fastest-growing element of Canadian health care spending, second only to hospital spending. Prescription drugs play an increasingly important role in Canada's health system. 300 million prescriptions are filled each year or an average of 10 per person per year. Prescription drugs accounted for 5.8% of total health care spending in 1980 and 13% of total health care spending in 2003. A primary long term goal of this proposal is to develop a decision support system for evidence-based management, quality control and best practice recommendations in the area of medical prescriptions, broadly conceived. Results of our research will improve accessibility, management and manipulation of information in a networked environment by: 1. building an application prototype for adaptive information extraction (IE), text & data mining from (online) documents to find evidence on which to base best practice recommendations; and 2. employing multiply sectioned Bayesian networks (MSBNs) to infer a probabilistic interpretation to validate evidence for recommendations (MSBNs provide a framework for probabilistic inference). We collaborate with COMPUS, a national program that defines best practices to drug prescribing/use that, based on evidence, is clinically and cost-effective; and contributes to optimal health outcomes. Best practices improve drug-related health outcomes; patients' quality of life; and cost-effective use of medications by changing knowledge and behavior. Evidence is based on research from published and unpublished literature.

Biography
Nick Cercone is Professor and Dean of the Faculty of Science & Engineering at York University. Prior to that he was Dean of the Faculty of Computer Science at Dalhousie University in Halifax, Nova Scotia, Canada from 2002-2006. He was Chair of Computer Science at the University of Waterloo from 1997-2002. From 1993 until 1997 he was Associate Vice President (Research), Dean of Graduate Studies and International Liaison Officer at the University or Regina. Formerly he was Director of the Centre for Systems Science at Simon Fraser University (1987-1992) and chairman of the School of Computing Science (1980-1985) at Si­mon Fraser. Cercone’s research interests include natural language processing, knowledge-based systems, knowledge-discovery in databases, data mining, and design and human interfaces. He is the author of over 300 refer­eed publications and has graduated 70 graduate students. Cercone co-founded Computational Intelligence, edits Knowledge and Information Systems, and serves on the editorial board of six journals. He is a member of the ACM, IEEE, AAAI, AISB, AGS, and ACL, and a past president of the CSCSI/SCEIO (Canadian Society for Computational Studies of Intelligence), of the Canadian Society for Fifth Generation Research, and of the Canadian Association for Computer Science (CACS/AIC). Cercone served on the Canadian Ge­nome Assessment and Technology Board, the CANARIE Board, CanWest, the Institute for Robotics and In­telligent Systems (IRIS) Research Committee, the Saskatchewan Research Council Board, and the Regina Economic Development Authority (information technology). Cercone also serves on NSERC, CFI, CHRP, CRC, CITO and NSF committees, and in 1996 he won the Canadian Artificial Intelligence Society's Distinguished Service Award. In 2002 Cercone became a Fellow of the IEEE for contributions to Knowledge Discovery. He has won two best paper awards. Cercone received the BS degree in Engineering Science from the University of Steubenville in 1968, the MS degree in Computer and Information Science from Ohio State University.

********* ALL INTERESTED ARE WELCOME ***********
(For enquiry, please contact Computer Science Department at 3411 2385)

http://www.comp.hkbu.edu.hk/v1/?page=seminars&id=29&lang=sc
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