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Technique hybride pour la classification associative des maladies cardiaques

Technique hybride pour la classification associative des maladies cardiaques


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About the Book

Au cours des dernières années, le secteur des soins de santé a collecté d'énormes quantités de données qui, malheureusement, ne sont pas extraites pour découvrir des informations cachées permettant une prise de décision efficace. Aujourd'hui, les services médicaux ont parcouru un long chemin pour traiter les patients atteints de diverses maladies. L'une des plus mortelles est la maladie cardiaque, qui ne peut être vue à l'oeil nu et survient instantanément. Le taux de mortalité a augmenté en raison de mauvaises décisions cliniques. Pour parvenir à un traitement fiable et rentable, des systèmes d'information ou d'aide à la décision basés sur l'informatique peuvent être développés pour accomplir cette tâche. L'exploration de données fournit la solution pour la découverte de connaissances à partir de ces bases de données vastes et complexes. Le travail de l'auteur implique le développement d'un cadre basé sur des techniques de classification associative sur un ensemble de données cardiaques. La mise en oeuvre du travail est effectuée sur l'ensemble de données cardiaques de l'UCI Machine Learning Repository afin de tester et d'évaluer différentes méthodes pour obtenir de meilleurs résultats. Les résultats expérimentaux montrent que la plupart des règles de classification associative aident à la meilleure prédiction des maladies cardiaques et à la création d'un système d'aide à la décision fiable.


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Product Details
  • ISBN-13: 9786207242092
  • Publisher: KS Omniscriptum Publishing
  • Binding: Paperback
  • Language: French
  • Returnable: N
  • Weight: 145 gr
  • ISBN-10: 6207242092
  • Publisher Date: 12 Mar 2024
  • Height: 229 mm
  • No of Pages: 56
  • Spine Width: 3 mm
  • Width: 152 mm


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