scholarly journals Survey on Privacy Preservation in Big Data for Healthcare Monitoring

2018 ◽  
Vol 7 (4.19) ◽  
pp. 1021
Author(s):  
Mangore Anirudh K ◽  
Dr. M Roberts Masillamani
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Privacy Preservation ◽  
Healthcare Providers ◽  
Big Data Analytics ◽  
Database Access ◽  
Health Monitoring System ◽  
Privacy Requirements ◽  
Care Services ◽  
Healthcare Monitoring

This paper represents the prototype of  health monitoring system using Big Data. this brings several Advantage  to the healthcare industry by way of providing timely patient care services, proactive disease detection, real-time monitoring among others. The major challenge faced by healthcare providers on safeguarding the confidentiality of patients’ data.if confidentiality is not well maintained, people may be unable to share their data. Because security has been investigated as a new dimension, “veracity,” in big data, we aim to exploit new challenges of big data in terms of security and devote our attention toward efficient and privacy-preserving computing in the big data era. Specifically, we primary formalize the basic architecture of big data analytics, identify the corresponding privacy requirements, and introduce an efficient and privacy Triple DES as an example in response to data mining’s efficiency and privacy requirements in the big data era. The results of this research exhibit that the proposed system has better secured database access and maintain privacy for all patient data than the traditional database. 

scholarly journals The Benefits of Big Data Analytics in the Healthcare Sector

2015 ◽  
pp. 406-439 ◽  
Author(s):  
Andrea Darrel ◽  
Margee Hume ◽  
Timothy Hardie ◽  
Jeffery Soar
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Healthcare Providers ◽  
Big Data Analytics ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Healthcare Sector ◽  
Improved Outcomes ◽  
Health Initiatives ◽  
Remote Patient

The benefits of big data analytics in the healthcare sector are assumed to be substantial, and early proponents have been very enthusiastic (Chen, Chiang, & Storey, 2012), but little research has been carried out to confirm just what those benefits are, and to whom they accrue (Bollier, 2010). This chapter presents an overview of existing literature that demonstrates quantifiable, measurable benefits of big data analytics, confirmed by researchers across a variety of healthcare disciplines. The chapter examines aspects of clinical operations in healthcare including Cost Effectiveness Research (CER), Clinical Decision Support Systems (CDS), Remote Patient Monitoring (RPM), Personalized Medicine (PM), as well as several public health initiatives. This examination is in the context of searching for the benefits described resulting from the deployment of big data analytics. Results indicate the principle benefits are delivered in terms of improved outcomes for patients and lower costs for healthcare providers.

Real Time Analysis Based on Intelligent Applications of Big Data and IoT in Smart Health Care Systems

2020 ◽  
pp. 1839-1857
Author(s):  
Mamata Rath
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Treatment Plan ◽  
Big Data Analytics ◽  
Data Sets ◽  
Care Services ◽  
Real Time Analysis ◽  
Health Care Applications ◽  
Care Systems

Currently, there is an expanding interest for additional medical data from patients about their healthcare choices and related decisions, and they further need investment in their basic health issues. Big data provides patients presumptuous data to help them settle on the best choice and align with their medicinal treatment plan. One of the very advanced concepts related to the synthesis of big data sets to reveal the hidden pattern in them is big data analytics. It involves demanding techniques to mine and extract relevant data that includes the actions of piercing a database, effectively mine the data, query and inspect the data and is committed to enhance the technical execution of various task segments. The capacity to synthesize a lot of data can enable an association to manage data that can influence the business. In this way, the primary goal of big data analytics is to help business relationships to have enhanced comprehension of data, and subsequently, settle on proficient and very much educated decisions. Big data analytics empowers data diggers and researchers to examine an extensive volume of data that may not be outfit utilizing customary apparatuses. Big data analytics require advances and statistical instruments that can change a lot of organized, unstructured, and semi-organized data into more reasonable data and metadata designed for explanatory procedures. There is tremendous positive potential concerning the application of big data in human health care services and many related major applications are still in their developmental stages. The deployment of big data in health service demonstrates enhancing health care results and controlling the expenses of common people due to treatment, as proven by some developing use cases. Keeping in view such powerful processing capacity of big data analytics in various technical fields of modern civilization related to health care, the current research article presents a comprehensive study and investigation on big data analytics and its application in multiple sectors of society with significance in health care applications.

Big Data Analytics of IoT-Based Cloud System Framework: Smart Healthcare Monitoring Systems

2022 ◽  
pp. 181-208
Author(s):  
Joseph Bamidele Awotunde ◽  
Rasheed Gbenga Jimoh ◽  
Roseline Oluwaseun Ogundokun ◽  
Sanjay Misra ◽  
Oluwakemi Christiana Abikoye
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Cloud System ◽  
Monitoring Systems ◽  
System Framework ◽  
Smart Healthcare ◽  
Healthcare Monitoring

scholarly journals Privacy preservation techniques in big data analytics: a survey

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
P. Ram Mohan Rao ◽  
S. Murali Krishna ◽  
A. P. Siva Kumar
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Privacy Preservation ◽  
Big Data Analytics

scholarly journals The Benefits of Big Data Analytics in the Healthcare Sector

2016 ◽  
pp. 842-875 ◽  
Author(s):  
Andrea Darrel ◽  
Margee Hume ◽  
Timothy Hardie ◽  
Jeffery Soar
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Healthcare Providers ◽  
Big Data Analytics ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Healthcare Sector ◽  
Improved Outcomes ◽  
Health Initiatives ◽  
Remote Patient

The benefits of big data analytics in the healthcare sector are assumed to be substantial, and early proponents have been very enthusiastic (Chen, Chiang, & Storey, 2012), but little research has been carried out to confirm just what those benefits are, and to whom they accrue (Bollier, 2010). This chapter presents an overview of existing literature that demonstrates quantifiable, measurable benefits of big data analytics, confirmed by researchers across a variety of healthcare disciplines. The chapter examines aspects of clinical operations in healthcare including Cost Effectiveness Research (CER), Clinical Decision Support Systems (CDS), Remote Patient Monitoring (RPM), Personalized Medicine (PM), as well as several public health initiatives. This examination is in the context of searching for the benefits described resulting from the deployment of big data analytics. Results indicate the principle benefits are delivered in terms of improved outcomes for patients and lower costs for healthcare providers.

Privacy Preservation in Big Data Analytics

2021 ◽  
pp. 1-22
Author(s):  
Yu-Chuan Tsai ◽  
Shyue-Liang Wang ◽  
Tzung-Pei Hong
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Privacy Preservation ◽  
Big Data Analytics

An Adoption model for a big data analytics system for improving healthcare services in Burundi’s public hospitals

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Yves Habimana ◽  
Irene Moseti-Morara ◽  
Damaris Odero
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Health Care Services ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Public Hospitals ◽  
Assessment Tools ◽  
Care Services ◽  
Adoption Model

One of the key responsibilities of a government is to provide efficient health care services that are better and affordable. In Burundi, patients’ health records are collected using handwritten forms and stored in filing cabinets. Evidence’ based research and practice shows that adoption of a Big Data Analytics (BDA) system can significantly improve health care services. Unfortunately, BDA adoption models and automated assessment tools are lacking not to mention the dearth caused by researchers’ predominant focus on the technical aspects. Therefore, the aim of this study was to propose a BDA system adoption model for improving health care services in Burundi’s public hospitals. This was achieved through a mixed research method a large part being qualitative. The factors that influence the adoption of BDA in public healthcare services using the Technology Organization Environment (TOE) adoption theory through a desk research. Semi-structured interviews, observations and document reviews were used to investigate the methods used to collect, store and analyze data in Public hospitals of Burundi. Afterwards, a web based automated Adoption Readiness Assessment Tool (ARAT) was developed then used to assess the readiness of Burundi in adopting a BDA system in its public hospitals. The assessment results showed that the country has adequate telecommunication infrastructures and has started using information systems like OpenClinic and District Health Information Software 2 (DHIS2) in some public hospitals, the government has set up policies for e-Health and the level of awareness is high as well among health workers. But there are improvements to be made in order to assure that the adoption is successful. Lastly, a tailored adoption model was proposed describing what should be done and how in order to assure a successful adoption of a BDA in public hospitals.  

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