A Machine Learning Model for Improving Healthcare on Cloud Computing

CHF 62.35
Auf Lager
SKU
3D6GQVRHS8G
Stock 1 Verfügbar
Geliefert zwischen Fr., 27.02.2026 und Mo., 02.03.2026

Details

Recently, cloud computing gained an important role in healthcare services due to its ability to improve the healthcare performance. However, the optimal selection of virtual machines to process a medical request represents a big challenge. For that, it proposes a new model for healthcare based on cloud environment using Parallel Particle Swarm Optimization to optimize the virtual machines selection. In addition, a new model for chronic kidney disease diagnosis and prediction is proposed to measure the performance of our virtual machines model. The prediction model of chronic kidney disease is implemented using two consecutive techniques, which are linear regression and neural network.

Autorentext

Ahmed Abdelaziz received his Ph.D. degree in information systems. He is mainly interested in machine learning, cloud computing, big data and healthcare services. He has several publications in reputed and high impact journals published by Elsevier, and others. He worked as an assistant professor at higher technological institute, Cairo, Egypt.

Weitere Informationen

  • Allgemeine Informationen
    • Sprache Englisch
    • Anzahl Seiten 116
    • Herausgeber LAP LAMBERT Academic Publishing
    • Gewicht 191g
    • Autor Ahmed Abdelaziz Mohamed
    • Titel A Machine Learning Model for Improving Healthcare on Cloud Computing
    • Veröffentlichung 12.08.2019
    • ISBN 3659539244
    • Format Kartonierter Einband
    • EAN 9783659539244
    • Jahr 2019
    • Größe H220mm x B150mm x T8mm
    • GTIN 09783659539244

Bewertungen

Schreiben Sie eine Bewertung
Nur registrierte Benutzer können Bewertungen schreiben. Bitte loggen Sie sich ein oder erstellen Sie ein Konto.
Made with ♥ in Switzerland | ©2025 Avento by Gametime AG
Gametime AG | Hohlstrasse 216 | 8004 Zürich | Schweiz | UID: CHE-112.967.470
Kundenservice: customerservice@avento.shop | Tel: +41 44 248 38 38