The healthcare industry collects huge amounts of data which, unfortunately, are not turned into useful information for effective decision making. Decision support systems (DSS) can now use advanced technologies such as On-Line Analytical Processing (OLAP) and data mining to deliver advanced capabilities. This paper presents a prototype clinical decision support system which combines the strengt...

background: a cross sectional study conducted to identify the organizational factors associated to the occupational stress among lecturers in selected community colleges, peninsular malaysia. methods: study was conducted by using cluster-sampling method and 189 self-administrated questionnaires were distributed. a validated malay version of job content questionnaire (jcq) was used to obtain the...

the management and analysis of flood hazards is of great socio- economic and ecological importance as it was estimated that 50 percent of word’s population resides and works within the costal zone till 2030. the management of coastal flood hazard reflects the cumulative effects and criteria more than the human mind can handle effectively. the flood management requires decision making for rela...

making decision has become one of the most challenging responsibilities of managers in recent decades. finding the optimum solution for multiple criteria decision making problems is complicated. notably, multiplicity of decision making indices accompanied by variability in quantitative and qualitative measures aggregates the complexity of decisions. operations research (or) and multiple criteri...

As the Army increases its focus on decisive action, more units are emphasizing decision-support templates and matrices as part of the planning process. Unfortunately, these tools have only minimally impacted tactical decision-making and mission outcomes because leaders are using these tools as another synchronization tool rather than focusing on decision points. When used correctly, decision-su...

Traditional techniques of data analysis do not enable the solution of all kind of problems and for that reason they have become insufficient. This caused a new interdisciplinary field of data mining to arise, encompassing both classical statistical, and modern machine learning techniques to support the data analysis and knowledge discovery from data. Data mining methods are powerful in dealing ...