PREDICTIVE ANALYTICS OF HEALTHCARE DATA
DOI:
https://doi.org/10.22159/ajpcr.2017.v10s1.19750Keywords:
Predictive Analytics, Machine Learning, Nil, Logistic Regression, Random ForestAbstract
Predictive analytics is employed to improve the ability to take precautionary measures during medical emergencies. In health care, the sensor-based
data are generated daily which can be used to predict future data using regression model. In this paper, pain dataset from integrating data for analysis,
anonimyzation, and sharing repository is used for experimenting different machine algorithms. The results show that logistic regression gives more
accuracy than other algorithms.
Downloads
References
Mukherjee A, Pal A, Misra P. Data analytics in ubiquitous sensor-based health information systems. In: Next Generation Mobile Applications, Services and Technologies (NGMAST). 6 International Conference on
IEEE, September; 2012. p. 193-8. th
Poh N, Tirunagari S, Windridge D. Challenges in designing an online healthcare platform for personalised patient analytics. In:Computational Intelligence in Big Data (CIBD), IEEE Symposium on
IEEE, December; 2014. p. 1-6.
Zaharia M, Chowdhury M, Franklin MJ, Shenker S, Stoica I.Spark: Cluster computing with working sets. In: Proceedings of the 2 USENIX Conference on Hot Topics in Cloud Computing. Vol. 10. June; 2010. p. 10.
nd
Available from: http://www.biostat.jhsph.edu/~fdominic/teaching/bio655/data/data.html.
Available from: http://www.biostat.jhsph.edu/~fdominic/teaching/bio655/data/text/back.raw.
DOI: 10.15147/J2QP4X.
Published
How to Cite
Issue
Section
The publication is licensed under CC By and is open access. Copyright is with author and allowed to retain publishing rights without restrictions.