Cloud Based Framework for Handling Diabetes Data: The storage of data online in the cloud - Couverture souple

P., Sangeetha; M., Kavitha

Couverture souple

ISBN 10 : 620475081X ISBN 13 : 9786204750811

Editeur : LAP LAMBERT Academic Publishing, 2022

Synopsis

With the exponential growth of data from various social networks like Facebook, Twitter, Mobile applications, Digital cameras, Sensor networks etc., and also from biomedical researches the overall data volume has increased tremendously. So analysing and extracting fruitful information from such a dynamic data is very much challenging task today. Data mining plays a vital role in handling big data for analysing pattern recognition and medical predictions. We can mine data using various algorithms and techniques such as Classification, Clustering, Regression, Association Rules, etc., These patterns can be utilized for fast and better clinical decision making of preventive and suggestive medicine. It implements an efficient data mining techniques called Frequent Pattern-Growth algorithm (FP-Growth) to analyse the diabetes data set have been collected from various patients and generated useful prediction results. Files stored in the cloud can be accessed at any time from any place so long as you have Internet access. So cloud stores the diabetes data sets and generates useful prediction results using FP-Growth algorithm.

Détails de l'édition

• Éditeur: LAP LAMBERT Academic Publishing
• Date d'édition: 2022
• Langue: anglais
• ISBN 10: 620475081X
• ISBN 13: 9786204750811
• Reliure: Broché
• Nombre de pages: 52
• Coordonnées du fabricant: non disponible
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