## 4 Expert System and Decision Support System  
A decision support system (DSS) is an information system developed to support judgments and courses of action in an organization or a business. A DSS often screens and analyzes an enormous quantity of data, gathering comprehensive information that is useful to solve problems and in making informed decisions. In recent years, several organizations have provided a growing array of software packages using DSS to support management decision-making. This significant development has been intensified using personal computers, developments in database management systems and the introduction of \"user-friendly\" device interface techniques. A decision support system presents some advantages to its users. Research has shown and substantiated a decreased decision cycle time, improved employee engagement and more reliable decision-making knowledge for all types of decision support systems. The time savings reported by using computerized support for decision-making are often  
Figure 3: A typical ECG waveform for one cardiac cycle measured from the lead II position. significant. Another cogent advantage is enhanced effectiveness. Most studies have analyzed soft measures such as perceived consistency of judgment rather than quantitative measures. DSS also provides users with improved interpersonal communication; it can enhance coordination and cooperation between decision-makers. Communication-driven and group DSS have shown that effect in so many circumstances. The improved usability of data is also a significant impetus for developing a DSS powered by data. Worthy to note is the advantage of reduced expenses; some analyses and case studies have reported low costs for DSS from labor savings in decision-making and reduced infrastructure costs. Moreover, from another perspective, learning occurs as a by-product of a DSS being used initially and continuously. Two forms of learning tend to occur: learning new ideas and gaining a deeper understanding of business facts for decision-making. In fact, some DSS serve as de facto tools for training new employees. An expert system is a knowledge-driven application that usually models human knowledge to perform certain tasks in a particular problem domain. The systems process expert knowledge and seek to imitate their ideas, abilities and intuitions. The definition of the expert system is generally based on the premise that the information of an expert can be stored in computer memory and implemented by a non-expert user. [PERSON] et al. [118] stated that the distinctive characteristic of the expert system has an insightful capacity to analyze its logic and justify its decisions. An expert system is composed of several parts: a knowledgebase where the expert information resides, a domain-specific computer providing various types of inferences, an effective user interface, the query and the advice generated by the system [118]. The structure of an expert system is depicted in Figure 4, and each of its components is briefly introduced in the following subsection. **Knowledgebase:** the knowledgebase is considered the core of the expert system; it comprises rules and facts that model expert knowledge about the problem domain. It is a domain-specific information repository gathered from the human expert via the acquisition of knowledge. An expert system's knowledgebase includes both empirical and heuristic knowledge. It replicates the expert's knowledge in the form of rules of development, frames logic, etc. [119]. **Inference Engine:** a significant element of any expert system is the inference engine. The inference engine is the component that determines how the expert system suitably interprets the information in the knowledgebase. Its function is to work with the system and user data available to generate solutions to problems; extract knowledge and produce answers, predictions and recommendations from the database just as a human expert does.