5G Enabled Electronic Health (E-Health) Computing

Ugochukwu O. Matthew

ISBN 10: 6206740404 / ISBN 13: 9786206740407

Published by LAP LAMBERT Academic Publishing Jul 2023, 2023

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -This book highlighted requirements for the effective implementation of smart healthcare systems for particular 5G scenarios. The study found that bimodal sensor access using an Artificial Neural Network computer algorithm can be used to execute data mining techniques and their applications in smart e-healthcare services for risk management, fraud detection, and client retention. In order to meet the demand for user-oriented medical services reform, the bimodal sensor electronic health (E-Health) record retrieval system is required to enhance the phenomenon for information management between healthcare consultants and patients. The creation of an E-Health data warehouse will make it possible for future medical smart devices to communicate with one another and to aggregate records from various heterogeneous database sources in order to meet the diversity requirements of medical and E-Health management, which will hasten and reinforce the advancement of health information technology in the medical field and healthcare organizations. The integration of a cloud-based IoT data warehousing platform was intended to facilitate global device connectivity management for e-healthcare.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 200 pp. Englisch.

Seller Inventory # 9786206740407

Bibliographic Details

• Title: 5G Enabled Electronic Health (E-Health) Computing
• Publisher: LAP LAMBERT Academic Publishing Jul 2023
• Publication Date: 2023
• Language: English
• ISBN 10: 6206740404
• ISBN 13: 9786206740407
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 13D millimeters 220 millimeters width by 150 millimeters height by 13 millimeters depth
• Weight: 316 grams

About this title

Synopsis

This book highlighted requirements for the effective implementation of smart healthcare systems for particular 5G scenarios. The study found that bimodal sensor access using an Artificial Neural Network computer algorithm can be used to execute data mining techniques and their applications in smart e-healthcare services for risk management, fraud detection, and client retention. In order to meet the demand for user-oriented medical services reform, the bimodal sensor electronic health (E-Health) record retrieval system is required to enhance the phenomenon for information management between healthcare consultants and patients. The creation of an E-Health data warehouse will make it possible for future medical smart devices to communicate with one another and to aggregate records from various heterogeneous database sources in order to meet the diversity requirements of medical and E-Health management, which will hasten and reinforce the advancement of health information technology in the medical field and healthcare organizations. The integration of a cloud-based IoT data warehousing platform was intended to facilitate global device connectivity management for e-healthcare.