Research Area:  Big Data

Abstract:

The health sector generates a large amount of medical data related to patient care, patient security, medical data privacy, drugs, and treatment effectiveness. This encourages researchers to pay attention to health analytics to develop effective medical policies and standards. Medical data are big data, so cost-effective intelligent solutions are required for complex health-related problems that further assist doctors or health practitioners in decision making and removing old medical practices that are on the verge of being obsolete. Complete, accurate, correct, and structured data are required to highlight current drawbacks in health practices and to accommodate new policies and procedures to upgrade healthcare services. This chapter explores various studies for the use of big data analytics in health science along with the application of big data tools and techniques in the biomedical sector. Notable rudimentary subdomains in intelligent computing for enhancing health services are big data analytics, bioinformatics, data mining, machine learning, and computer vision. The presented research work may further be utilized by health practitioners or researchers to explore the area of big data analytics in medical science in the direction of disease prediction, drug suggestion, treatment effectiveness, and online health monitoring.

Keywords:  
Big data analytics
Healthcare
Machine learning
Data-oriented techniques
Data mining
Applications

Author(s) Name:  Chinmay Chakraborty, Megha Rathi

Publisher name:  Elsevier

DOI:  10.1016/B978-0-12-821633-0.00009-X

Volume Information:  Pages 17-32

Paper Link:   https://www.sciencedirect.com/science/article/pii/B978012821633000009X