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Another example of a diagnosis rule-based expert system is EMERGE designed to be used in an emergency room. This system uses a form of production rules which incorporates weighing factors which are determined by a neural network. The neural network is composed of input and output blocks with a hidden layer block in between which communicates input to the output. The neural network learns from examples then predicts an output based on this knowledge. This system also uses an IF-THEN-UNLESS statement instead of an IF-THEN statement. Because of this, the decision process may be more precise, the results may be more accurate and the explanations may be better understood. A specific example from EMERGE using the IF-THEN and the IF-THEN-UNLESS indicates that the latter case is more compact and less complicated.
MYCIN was used for medical diagnosis (for a specific group of diseases).
PROSPECTOR evaluated geological sites for commercial development.
DENDRAL helped to infer a molecule’s structure given its chemical formula and other data.
XCON was developed to customize a network system to meet the customer’s needs.
MYCIN
http://people.dbmi.columbia.edu/~ehs7001/Buchanan-Shortliffe-1984/Chapter-01.pdf
http://psy.haifa.ac.il/~ep/Lecture%20Files/AI/Secure/Download/Introduction%20to%20expert%20systems%20-%20MYCIN.pdf
http://www.ijesi.org/papers/Vol(3)3/Version-1/G0331038042.pdf
CaDet
http://www.jcscm.net/fmgr/download.pdf?id=1755638&filename=paper.pdf
http://www.cancerprev.org/Journal/Issues/26/101/1291/4513
http://www.ncbi.nlm.nih.gov/pubmed/15542260
DXplain
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1560464/
GERMWATCHER
http://ds.ing.unife.it/~friguzzi/Papers/LamMelNan-ISMDA01.pdf
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2248498/
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1839697/
http://www.openclinical.org/aisp_germwatcher.html
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