An expert system for the evaluation of EDSS in multiple sclerosis

Mauro Gaspari, Gianluigi Roveda, Cinzia Scandellari, Sergio Stecchi

Research output: Contribution to journalArticle

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.

Original languageEnglish
Pages (from-to)187-210
Number of pages24
JournalArtificial Intelligence in Medicine
Volume25
Issue number2
DOIs
Publication statusPublished - 2002

Keywords

  • EDSS
  • Expanded Disability Status Scale
  • Expert system
  • Multiple sclerosis
  • Prolog

ASJC Scopus subject areas

  • Artificial Intelligence
  • Medicine(all)

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