De-Identified Personal Health Care System Using Hadoop

Madhavi, Dasari; Ramana, Bendi Venkata

doi:10.11591/ijece.v5i6.pp1492-1499

Cited by 9 publications

(6 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Madhavi and Ramana [30] used Hadoop and MapReduce to provide a solution that de-identifies personal health information. An advanced mechanism of using Map Reduce, UDF (User Data File), and Pig Queries was used in their application to be executed on the healthcare dataset and to protect the healthcare dataset.…”

Section: Big Data Analytics and Frameworkmentioning

confidence: 99%

Investigating the Adoption of Big Data Management in Healthcare in Jordan

Bani-Salameh

Al-Qawaqneh

Taamneh

2021

Data

View full text Add to dashboard Cite

Software developers and data scientists use and deal with big data to easily discover useful knowledge and find better solutions to improve healthcare services and patient safety. Big data analytics (BDA) is getting attention due to its role in decision-making across the healthcare field. Therefore, this article examines the adoption mechanism of big data analytics and management in healthcare organizations in Jordan. Additionally, it discusses health big data’s characteristics and the challenges, and limitations for health big data analytics and management in Jordan. This article proposes a conceptual framework that allows utilizing health big data. The proposed conceptual framework suggests a way to merge the existing health information system with the National Health Information Exchange (HIE), which might play a role in extracting insights from our massive datasets, increases the data availability and reduces waste in resources. When applying the framework, the collected data are processed to develop knowledge and support decision-making, which helps improve the health care quality for both the community and individuals by improving diagnosis, treatment, and other services.

show abstract

Section: Big Data Analytics and Frameworkmentioning

confidence: 99%

Investigating the Adoption of Big Data Management in Healthcare in Jordan

Bani-Salameh

Al-Qawaqneh

Taamneh

2021

Data

View full text Add to dashboard Cite

show abstract

“…Dasari Madhavi [27] provided a solution for de-identifying personal health information, Map Reduce application uses jar files which contain a combination of MR code and PIG queries. This application also uses advanced mechanism of using UDF (User Data File) which is used to protect the health care dataset.…”

Section: Related Workmentioning

confidence: 99%

A survey on health care data using Machine learning Algorithms

Manjulatha¹,

Pabboju²

2020

Preprint

View full text Add to dashboard Cite

Big data in the healthcare has been growing rapidly in recent years. A massive amount of patient’s data is generated through various sources in this digitalized environment including wearable devices, mobile devices, electronic health records and medical centres. The medical data, which are exploding exponentially includes a large volume of structured and unstructured data. Patients information is shared and managed by many sources such as insurance, in the form of prescription, healthcare providers including the attackers which causes a severe security threats their confidential data. Cybercriminals use a variety of social engineering attacks like phishing, leakage of data, embedding virus and trojan horse into the attachments, DNS snooping, sniffing, and many more. In this paper a brief overview is done on different data mining and security techniques which are implemented in healthcare data. The study and its presentation in this context would be helpful in not only analysing but also predicting chronic diseases depending upon the available stored data which has been collected from various sources in the area of medical expert system.

show abstract

“…Medical Information System already properly established in many countries, including Indonesia [9], [10]. It offers lucrative benefit such as increasing service availability and reliability to the patient and also diminishing expenditure [11].…”

Section: Current Researchmentioning

confidence: 99%

Information system to enhance medical services quality in Indonesia

Limanto

Andre

2019

IJECE

View full text Add to dashboard Cite

The consequence of disproportionate distribution and placement of Doctor in Indonesia is affecting people who live in rural area. Patient have to travel to city to receive medical treatment and must encounter another different problem such as: patients often have to wait a long time in the doctor's office even sometimes do not get the service because of holiday or rejected because the queue is full. Medical record in some cases may lost due in Indonesia mostly medical record recorded manually (paper based). Therefore doctor treatment is not optimal because doctor can no longer inspect patient illness history and any treatment that have been conducted before. This research proposes a new concept to help people who live in rural area to get better medical treatment. People could register and monitor doctor service queue via smart phone. System expanded with medical record management facilities to improve service quality of patient. Research object was doctor service in Sulawesi, Indonesia. This research indicates system could increase time efficiency, energy, and cost efficiency for patient and also the doctor. Additionally current system will be optimal if supported with stable internet network.

show abstract

De-Identified Personal Health Care System Using Hadoop

Cited by 9 publications

References 5 publications

Investigating the Adoption of Big Data Management in Healthcare in Jordan

Investigating the Adoption of Big Data Management in Healthcare in Jordan

A survey on health care data using Machine learning Algorithms

Information system to enhance medical services quality in Indonesia

Contact Info

Product

Resources

About