Hybrid Computational Intelligence for Handling Diagnosis of Aphasia

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

@InProceedings{Tsakonas:2001:EUNITEa,
  title =        "Hybrid Computational Intelligence for Handling
                 Diagnosis of Aphasia",
  author =       "Athanasios Tsakonas and Georgios Dounias and 
                 Diedrich {Graf Von Keyserlingk} and Hubertus Axer",
  booktitle =    "Proceedings of the CD-rom EUNITE-01, European
                 Symposium on Intelligent Technologies, Hybrid Systems
                 and their Implementation on Smart Adaptive Systems
                 Verlag-Mainz",
  year =         "2001",
  address =      "Tenerife, Spain",
  keywords =     "genetic algorithms, genetic programming, hybrid
                 computational intelligence, medical diagnosis, aphasia,
                 Aachen Aphasia Test",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.148.5734",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  contributor =  "CiteSeerX",
  language =     "en",
  oai =          "oai:CiteSeerXPSU:10.1.1.148.5734",
  abstract =     "This paper presents two models based on hybrid
                 computational intelligence, for the classification
                 between different types of aphasia. Aphasia is a human
                 syndrome, often due to brain damage. Its effects
                 usually are the patient's disability in the usage or
                 comprehension of words, as well as difficulties in
                 reading, or writing, or articulation. The proposed
                 methodology is mainly related to genetic programming,
                 an extension to the well-known genetic algorithms
                 approach. As a search methodology, genetic programming
                 is used in various domains, where symbolic regression
                 is needed. The hybrid methodology consists of the
                 genetic programming approach and a heuristic rule-based
                 scheme. The data used are nominal and ordinal,
                 corresponding to patient scorings valued in free
                 interviews by physicians. In most cases, the results
                 are competitive to the average human diagnosis.
                 Moreover, they are comprehensive by human experts,
                 enabling them to draw conclusions on the significance
                 of the patient scorings. The subjective nature of the
                 application domain, focuses the interest of the paper
                 into the acquired results, their interpretation and
                 their practical importance for the medical experts.",
  notes =        "http://www.elite-foundation.org/ELITE/programme%202001.htm",
}

Genetic Programming entries for Athanasios D Tsakonas Georgios Dounias Diedrich Graf von Keyserlingk Hubertus Axer

Citations