5G Enabled Electronic Health (E-Health) Computing
Artificial Intelligence & IoT Cloud Infrastructure
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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 he...
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 technologyin 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.
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