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Memorias de investigación
Conferences:
Rule Evolving System for Knee Lesion Prognosis from Medical Isokinetic Curves
Year:2009
Research Areas
  • Artificial intelligence
Information
Abstract
This paper proposes a system for applying data mining to a set of time series with medical information. The series represent an isokinetic curve that is obtained from a group of patients performing a knee exercise on an isokinetic machine. This system has two steps: the first one is to analyze the input time series in order to generate a simplified model of an isokinetic curve; the second step applies a grammar-guided genetic program including an evolutionary gradient operator and an entropybased fitness function to obtain a set of rules for a knowledge-based system. This system performs medical prognosis for knee injury detection. The results achieved have been statistically compared to another evolutionary approach that generates fuzzy rule-based systems.
International
Si
978-3-642-02266-1
Entity
Entity Nationality
Sin nacionalidad
Place
Participants
  • Coautor: José María Font Fernández (FI - UPM)
  • Autor: Daniel Manrique Gamo (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Inteligencia Artificial (LIA)
  • Departamento: Inteligencia Artificial
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