Medical Knowledge Discovery on the Meningoencephalitis Diagnosis Studied by the Cascade Model

: The cascade model is a rule induction methodology that uses level-wise expansion of a lattice. An attribute-value pair is expressed as an item, and every node in the lattice is specified by an itemset and by its supporting instances. If the distribution of the class attribute values shows a large change along a link in the lattice, the link is represented as a rule "IF item-along-link added on itemset-on-upper-node, THEN class-I". The strength of a rule is measured by its between-group sum of squares (BSS). Factors affecting diagnosis, the results of cultures, and prognosis are examined in a meningoencephalitis data set. Strong rules are expected to lead to new knowledge of the disease.

• Type: Conference
• Year: 2001
• Where: JSAI
• Authors: Takashi Okada
• Keywords: Artificial Intelligence, Class Attribute Values, Factors Affecting Diagnosis, JSAI 2001, Rule Induction Methodology