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Health Care Informatics Expert Systems Expert Systems Essay
Health Care Informatics
Expert Systems
Expert systems are always computer applications that tend to combine computer equipment, special information and software so that they imitate reasoning and advice of expert human. Being a part of artificial intelligence they offer discipline-specific advice as well as explanation to their users. Artificial intelligence covers a broad field of several aspects of computer generated thought, on the other hand, expert systems focuses narrowly. The area where expert systems will function well is with specific problems or activities as well as a discrete database of digitized rules, facts, models and cases. Based on the software program, it always integrates a searching and sorting program with a knowledge database. This specific searching plus sorting program for an expert system is called the inferent engine.
What makes inferent engine are the entire systematic processing rules and logic that are associated with task at hand. Mathematical probability serves as the core for most of the expert systems. The other component which is the knowledge database help in storing essential factual, procedural, as well as experiential information about expert knowledge. Using a procedure of knowledge transfer, expertise or the skills and knowledge that sustains a much better as compared to average performance, passes from human expert to knowledge engineer, (Liebowitz Jay, 1998). The work of the knowledge engineer then becomes creating and structuring the knowledge database through completing some of the logical, physical and psychosocial tasks. And this is why expert systems are always called knowledge-based information systems.
The different between expert systems and Decision Support System (DSS) do exist.DSS as a successor of Management Information Systems (MIS), have been traditionally following the decision logic line of thinking and incorporate MIS algorithmic tools in improving the choice activity of decision makers. This can be mathematical programming, optimization methods, and multi-criteria models among others. They tend to be structured related as they assume that decision problem is able to be formulated mathematically and do not stress information processing and display, (Turban, Efraim & Jay E. Aronson,1998).
This is contrary to expert system, being successors of the general problem solver; it follows more on the process paradigm of cognitive decision theory. They don't necessarily assume that the decision problem is able to be formulated in form of mathematical models, they substitute human expertise with the missing efficient algorithms and they do not have structure but they are context related, having much smaller domains of application as compared to decision support system,( Jackson Peter, 1998). Knowledge is signified in several diverse ways, for example rules, semantic nets, frames, among others. Knowledge is always processed within the inferent machines that work by performing symbol processing (truth values of antecedents, conclusions and others).
It wasn't long before the border between DSS and ES became…
Sample Source(s) Used
References
Jackson Peter, (1998). Introduction to Expert Systems. Addison Wesley. Retrieved March 14,
2012 from http://www.referenceforbusiness.com/encyclopedia/Ent-Fac/Expert-Systems.html#ixzz1p1ML8QPX
Liebowitz, Jay, (Ed)(1998). The Handbook of Applied Expert Systems. Boca Raton, FL: CRC
Press LLC. Retrieved March 14, 2012 from http://www.referenceforbusiness.com/encyclopedia/Ent-Fac/Expert-Systems.html#ixzz1p1ML8QPX
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1.3 Study Structure
Organization of the Study
The following five chapters constitute the body of Chapter I: Introduction
Chapter II: Review of the Literature
Chapter III: Methods and Results
Chapter IV: Chapter V: Conclusions, Recommendations, and