Archive System Using Big Data for Health care: Analysis, Architecture, and Implementation
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In the era of digitalization, since the last few decades, we have seen the advancements of technology in all the domains, and health care does not remain in situ. With the growing medical science field, the growth of the EMRs/EHRs skyrockets the growth of data. Hence, storing the patients’ data and reports has become an ache this day. This is often too large and heterogeneous, and changes are often to be stored, processed, and transformed into the required form, thus resulting in a lack of memory storage, processing power and bandwidth for transmission of the data. So hospitals are now lapsing into a dilemma for buying more storage and more processing power for preserving the patients’ data. The patients’ data not only includes textual data but also images, videos, and different files. This data can vary from patient to patient and differs from one hospital to another. In this paper, we will be talking about the room for the big data technology and data compression in the fields of medicine and healthcare by reduction in storage consumption, cleaning, and formatting the patients’ data. We can furthermore use this clean data for research and analytical purposes. Therefore, we will be proposing an architecture for the Patient Data Archiving System including Big data technologies and data compression technique through this paper.
KeywordsBig data Cassandra ETL PACS Storage techniques PostgreSQL CQL Clustering Network topology Image processing Image compression DICOM Feature extraction Analytics Health care Framework Methodology
We are grateful to Dr. Arvind Sharma, Zydus Hospital, Ahmedabad, and Dr. Gargey Sutaria, Shably Hospital, Ahmedabad, for the provision of expertise and technical support providing necessary guidance concerning the research. Without their superior knowledge and experience, the research would lack in quality of outcomes, and thus, their support has been essential.
- 3.PACS Storage Calculator - https://www.dicomlibrary.com/dicom/pacs-storagecalculator/
- 5.Dinov ID (2016) Methodological challenges and analytic opportunities for modeling and interpreting big healthcare data. Gigascience 5(1)Google Scholar
- 6.Wang W, Krishnan E (2014) Big data and clinicians: a review on the state of the science. JMIR Med Inform 2(1)Google Scholar
- 7.Panda M, Ali SM, Panda SK (2017) Big data in health care: a mobile-based solution. In: International conference on big data analytics and computational intelligence (ICBDAC). IEEEGoogle Scholar
- 8.Wilson DL (1995) Image compression requirements and standards in PACS. In: Proceedings of SPIE 2435, medical imaging: PACS design and evaluation: engineering and clinical issuesGoogle Scholar
- 10.Rumsfeld JS, Joynt KE, Maddox TM (2016) Big data analytics to improve cardiovascular care: promise and challenges. Nat Rev Cardiol 13(6)Google Scholar
- 11.Dataset - https://synthea.mitre.org/downloads
- 12.Al Hamid HA (2017) A security model for preserving the privacy of medical big data in a healthcare cloud using a fog computing facility with pairing-based cryptography. IEEE Access 5:22313–22328; Krishnan SM (2016) Application of analytics to big data in healthcare. In: 2016 32nd Southern biomedical engineering conference (SBEC). IEEEGoogle Scholar