approche de l'évaluation de l'ensemble des données EEG pour l'analyse des données du sommeil
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approche de l'évaluation de l'ensemble des données EEG pour l'analyse des données du sommeil

approche de l'évaluation de l'ensemble des données EEG pour l'analyse des données du sommeil


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About the Book

La bio-informatique devient de plus en plus populaire aujourd'hui car elle combine les problèmes médicaux avec le domaine technique des technologies de l'information pour identifier ou détecter les troubles médicaux dans le corps humain. Ce domaine est précieux tant pour les médecins que pour les développeurs de logiciels. Pour identifier les troubles cérébraux tels que l'épilepsie, les parasomnies chez les patients, les données EEG sont extraites de la source de données physionet où de nombreux ensembles de données sont disponibles pour les chercheurs. L'analyse de cet ensemble de données est effectuée par polyman qui est utilisé comme bibliothèque de traçage et outil de transformation pour transformer le format de données EDF en format de données ASCII. L'outil aide également à identifier les différents paramètres qui sont utiles pour les prédictions liées aux troubles du cerveau. Dans ce travail, un algorithme amélioré de régression par vecteur de support (SVR) a été développé et mis en oeuvre en utilisant le langage de programmation avancé Python et comparé à l'algorithme classique de machine à vecteur de support (SVM). Les résultats montrent une meilleure performance du SVR que du SVM en termes de complexité et de temps d'exécution.


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Product Details
  • ISBN-13: 9786205622278
  • Publisher: KS Omniscriptum Publishing
  • Publisher Imprint: Editions Notre Savoir
  • Height: 229 mm
  • No of Pages: 60
  • Spine Width: 4 mm
  • Width: 152 mm
  • ISBN-10: 6205622270
  • Publisher Date: 26 Jan 2023
  • Binding: Paperback
  • Language: French
  • Returnable: N
  • Weight: 150 gr


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