Future of Information and Communication Conference (FICC) 2025
28-29 April 2025
Publication Links
IJACSA
Special Issues
Future of Information and Communication Conference (FICC)
Computing Conference
Intelligent Systems Conference (IntelliSys)
Future Technologies Conference (FTC)
International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 6, 2017.
Abstract: Debate on big data analytics has earned a remarkable interest in industry as well as academia due to knowledge, information and wisdom extraction from big data. Big data and cloud computing are two most important trends that are defining the new emerging analytical tools. Big data has various applications in different fields like traffic control, weather forecasting, fraud detection, security, education enhancement and health care. Extraction of knowledge from large amount of data has become a challenging task. Similarly, big data analysis can be used for effective decision making in healthcare by some modification in existing machine learning algorithms. In this paper, rawbacks of existing machine learning algorithms are summarized for big data analysis in healthcare.
Muhammad Umer Sarwar, Muhammad Kashif Hanif, Ramzan Talib, Awais Mobeen and Muhammad Aslam, “A Survey of Big Data Analytics in Healthcare” International Journal of Advanced Computer Science and Applications(IJACSA), 8(6), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080646
@article{Sarwar2017,
title = {A Survey of Big Data Analytics in Healthcare},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080646},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080646},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {6},
author = {Muhammad Umer Sarwar and Muhammad Kashif Hanif and Ramzan Talib and Awais Mobeen and Muhammad Aslam}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.