Implementation and Analysis of Predictive Algorithms for Healthcare Data in Cloud Environment

Author(s):  
Savita K. Shetty ◽  
Annapurna P Patil
2022 ◽  
Vol 32 (2) ◽  
pp. 765-779
Author(s):  
Kirupa Shankar Komathi Maathavan ◽  
Santhi Venkatraman

2019 ◽  
Vol 108 (2) ◽  
pp. 1021-1035 ◽  
Author(s):  
V. Sri Vigna Hema ◽  
Ramesh Kesavan

2021 ◽  
Author(s):  
HariPriya K ◽  
Brintha NC ◽  
Yogesh C K

Security is a major concern in every technology that is introduced newly to facilitate the existing mechanism for better maintenance and handling. This is also the case in electronic health records. The data of the hospitals and the associated patients gets digital in the past few decades. The data is stored in the cloud for various reasons such as convenience of the participating entities to access it, easy maintenance. But, with this there also arises various security concerns. It has been observed from the reason studies that blockchain is used as the means of securing the healthcare data in the cloud environment.This study discusses the following. 1) Applications of blockchain in cloud environment, 2) Applications of blockchain in securing healthcare data 3) General issues and security concerns in blockchain technology and what features of block chain makes it suitable for securing health care a nd what features restricts it from using.This work helps the future researchers in getting a deep understanding of the in and out of applying blockchain in cloud and healthcare environment.


Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.


2016 ◽  
Vol 10 (1) ◽  
pp. 36
Author(s):  
Gregory J Dehmer ◽  

Public reporting of healthcare data is not a new concept. This initiative continues to proliferate as consumers and other stakeholders seek information on the quality and outcomes of care. Furthermore, mandates for the development of additional public reporting efforts are included in several new healthcare legislations such as the Affordable Care Act. Many current reporting programs rely heavily on administrative data as a surrogate for true clinical data, but this approach has well-defined limitations. Clinical data are traditionally more difficult and costly to collect, but more accurately reflect the clinical status of the patient, thus enhancing validity of the quality metrics and the reporting program. Several professional organizations have published policy statements articulating the main principles that should establish the foundation for public reporting programs in the future.


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