• Title of article

    An expert system for the evaluation of EDSS in multiple sclerosis

  • Author/Authors

    Gaspari، نويسنده , , Mauro and Roveda، نويسنده , , Gianluigi and Scandellari، نويسنده , , Cinzia and Stecchi، نويسنده , , Sergio، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2002
  • Pages
    24
  • From page
    187
  • To page
    210
  • Abstract
    Multiple sclerosis is a disease of unknown aetiology. Despite several advances in therapy in recent years, some problems such as the prognostic criteria are imperfectly understood. Several experimental trials of therapy in multiple sclerosis are in course in order to discover a successful treatment. Most of these research studies use a clinical rating scale named Expanded Disability Status Scale (EDSS) as an evaluation tool for the effects of drugs. This scale is defined by a set of rules written in English which provide a numerical quantification of the neurological examination. Although EDSS has been widely used for almost 20 years, its application still depends on the interpretation of the neurologist who performs the neurological examination, and many applications of the scale performed by different neurologist on the same patient can give different results. This is a serious problem for international trials because they lack of a reliable measure of the effects of drugs. Here, we present an expert system for the automatic evaluation of EDSS in multiple sclerosis, which has been developed to overcome this problem. The expert system exploits an explicit representation of EDSS rules, it is able to explain its conclusions and it provides a revision tool to support the user if no satisfying solution can be reached. Using this expert system, clinical trials based on EDSS can benefit of a more reliable evaluation tool providing more valuable results.
  • Keywords
    Multiple sclerosis , expanded disability status scale , EDSS , expert system , Prolog
  • Journal title
    Artificial Intelligence In Medicine
  • Serial Year
    2002
  • Journal title
    Artificial Intelligence In Medicine
  • Record number

    1835919