Investigation into the Application of Artificial Intelligence Methods to the Analysis of Medical Data

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@MastersThesis{setzkorn:masters,
  author =       "Christian Setzkorn",
  title =        "Investigation into the Application of Artificial
                 Intelligence Methods to the Analysis of Medical Data",
  school =       "Computer Science Department, University of Liverpool",
  year =         "2000",
  address =      "Peach Street, Liverpool L69 7ZF",
  month =        jan,
  email =        "C.Setzkorn@csc.liv.ac.uk, CSetzkorn@gmx.net",
  keywords =     "genetic algorithms, genetic programming, data mining",
  broken =       "http://www.csc.liv.ac.uk/~chris/Thesis_Setzkorn_Online.zip",
  broken =       "http://www.csc.liv.ac.uk/~chris/SE.html",
  size =         "219 pages",
  abstract =     "Two methods from the field of artificial intelligence
                 were implemented and employed on a medical data set, in
                 order to perform data mining. The data set consisted of
                 cases from patients who suffered recurring miscarriage,
                 and the aim was to investigate whether the implemented
                 methods were able to identify previously unknown
                 factors associated with recurrent miscarriage. The
                 first approach used a specific type of artificial
                 neural network - Kohonen's self-organizing map for
                 performing clustering within data sets. By using new
                 cluster detection methods and the visualisation
                 possibilities of the employed programming language
                 Java, and its graphical user interface components
                 Swing, it allows interactively the visualisation of
                 relationships within a data set. The second, relatively
                 unique approach, infers rules from a data set by using
                 the paradigm of genetic programming. The rules consist
                 of an IF-part (antecedent) and a THEN-part
                 (consequent). The system has to be supplied with the
                 consequent and works out antecedents, which describe
                 the sub data set indicated by the consequent within the
                 supplied data set. The antecedents produced take the
                 form of a tree where Boolean operations AND, OR and NOT
                 represent nodes, and Boolean expressions represent the
                 leaves. Boolean expressions can be built from all types
                 of data including free-text and real numbers. This
                 system was also implemented with Java and offers in
                 addition the possibility of knowledge extraction from
                 clusters built by the self-organizing map approach.",
  notes =        "My master thesis concerns (apart of other things) rule
                 inference from a medical data set by using GP (Data
                 Mining). The rules consist of an IF-part (antecedent)
                 and a THEN-part (consequent). The system has to be
                 supplied with the consequent and works out antecedents,
                 which describe the sub data set indicated by the
                 consequent within the supplied data set. The
                 antecedents produced take the form of a tree where
                 Boolean operations AND, OR and NOT represent nodes, and
                 Boolean expressions represent the leaves. Boolean
                 expressions can be built from all types of data
                 including free-text and real numbers (AGE<=35,
                 DiseaseXYZ = yes, bloo_valueX = abnormal values). This
                 system was implemented with Java and offers in addition
                 the possibility of knowledge extraction from clusters
                 built by a self-organizing map approach (also
                 implemented during this thesis).",
}

Genetic Programming entries for Christian Setzkorn

Citations