The Role And Challenges Of Big Data In Healthcare Informatics And Analytics: Review
Abstract
Background: Data science is an interdisciplinary discipline that employs big data, machine learning algorithms, data mining techniques, and scientific methodologies to extract insights and information from massive amounts of structured and unstructured data. The healthcare industry constantly creates large, important databases on patient demographics, treatment plans, and results of medical exams, insurance coverage, and more. Moreover, healthcare has evolved with the development of technology to improve the quality of life and save lives. Today, big data is considered as one of the most essential and promising future technology areas and has been attracting the medical community’s attention. As a result of big data, we can improve patient outcomes, personalize care, improve relationships between the patient and the provider, and decrease hospital costs. The effect of big data is very large since medical societies are known for their size, diversity of complexity, and a high degree of dynamism. Big data has been discussed from different viewpoints in recent years, protecting its involvement in many aspects, specifically those related to the healthcare system. Assembling health information, sharing data, and integrating health are essential in spreading health care. In addition, the security and privacy of data are critical since the data must be accessed from multiple locations within the distributed system. This paper review aims to recognize the role of big data in healthcare issues aggregating data and the challenges associated with big data in healthcare. The papers that have been selected for review are from last year’s research.
Metrics
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
CC Attribution-NonCommercial-NoDerivatives 4.0