Abstract
Expert systems, or decision support systems, are artificial intelligence systems that have been trained with real cases to perform complicated tasks. They are used in a variety of areas and are among the most popular application fields in artificial intelligence. Expert systems have applications in different areas of medicine. Here we present a short history of medical expert systems and the characteristics of these systems. Medical expert systems were initially developed for academic areas and later for clinical applications also. Health care systems produce tremendous amounts of information (patient, demographic, clinical and billing data), which are susceptible to analysis by intelligent software and need new techniques to extract new knowledge. A variety of medical expert systems tools are available and can function as intelligent assistants to clinicians, helping in diagnostic processes, laboratory analysis, treatment protocol, and teaching of medical students and residents. A critical review of the strengths and limitations, as well as the latest trends in decision support systems, is discussed. In addition, a model for computer-based medical diagnoses of primary immunodeficiencies is presented.
Keywords: Knowledge-based systems, artificial intelligence, data mining, machine learning, immunodeficiencies, decision support systems, PIDexpert
Current Bioinformatics
Title: Medical Expert Systems
Volume: 3 Issue: 1
Author(s): Mauno Vihinen and Crina Samarghitean
Affiliation:
Keywords: Knowledge-based systems, artificial intelligence, data mining, machine learning, immunodeficiencies, decision support systems, PIDexpert
Abstract: Expert systems, or decision support systems, are artificial intelligence systems that have been trained with real cases to perform complicated tasks. They are used in a variety of areas and are among the most popular application fields in artificial intelligence. Expert systems have applications in different areas of medicine. Here we present a short history of medical expert systems and the characteristics of these systems. Medical expert systems were initially developed for academic areas and later for clinical applications also. Health care systems produce tremendous amounts of information (patient, demographic, clinical and billing data), which are susceptible to analysis by intelligent software and need new techniques to extract new knowledge. A variety of medical expert systems tools are available and can function as intelligent assistants to clinicians, helping in diagnostic processes, laboratory analysis, treatment protocol, and teaching of medical students and residents. A critical review of the strengths and limitations, as well as the latest trends in decision support systems, is discussed. In addition, a model for computer-based medical diagnoses of primary immunodeficiencies is presented.
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Cite this article as:
Vihinen Mauno and Samarghitean Crina, Medical Expert Systems, Current Bioinformatics 2008; 3 (1) . https://dx.doi.org/10.2174/157489308783329869
DOI https://dx.doi.org/10.2174/157489308783329869 |
Print ISSN 1574-8936 |
Publisher Name Bentham Science Publisher |
Online ISSN 2212-392X |
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