Abstract: Nowadays, detection and prevention of adverse drug events (ADEs) is a vital problem in healthcare. Information systems have the potential to detect and minimize ADEs in a timely and cost-effective way to prevent patient harm. Based on extensive literature review, this paper reviews and categorizes different information systems used to detect ADEs including traditional information systems, modeling and simulation, clinical decision support systems, trigger tools and alerting systems, data mining systems, rule-based expert systems, natural language, artificial neural network and fuzzy logic. This paper recommends new strategies to encourage more research and development of intelligence systems to detect ADEs.
Abstract: This paper aims to use an application-oriented and domain-specific benchmark called "Transaction Processing over XML" (TPoX). It exercises all aspects of XML databases, including storage, indexing, logging, transaction processing, and concurrency control. TPoX simulates a financial multi-user workload with XML data conforming to the FIXML standard. This paper also describes TPoX and presents early performance results for DB2 and Oracle databases. The main results showed that the performance of DB2 is much better than the performance of Oracle.