Comparison Analysis on Medical Data Mining for Drug Suggestion

Authors

  • M. Robinson Joel  Department of CSE, SMK Fomra Institute of Technology, Tamil Nadu, India
  • Gandhi Jabakuma  Department of CSE, SMK Fomra Institute of Technology, Tamil Nadu, India
  • W. Mercy  Department of CSE, Agni College of Engineering, Tamil Nadu, India

DOI:

https://doi.org//10.32628/IJSRSET196157

Keywords:

Medical Data Mining, Drug Safety Assessment, MGPS, FDA, FUZZY Logic

Abstract

The drug back reaction measurement is the most important part of the drug safety assessment. In the early days, the measurement is made by trailing the impact after the course of many examples. In the pharmaceutical industries, the most interesting research topic is adverse drug detection which rules the world. In the 21century , the data available in the medical field gave an important development in motivating of an adverse event. Recently, many people put forward the statistical data and also the mining methods which are largely implemented to detect the drug adverse event. In the following paper, we explain more methods explained by expert’s researchers in the dynamic domain of data.

References

  1. A. Szarfman, J.M. Tonning, and P.M. Doraiswamy, “Pharmacovigilance in the 21st Century: New Systematic Tools for an Old Problem,” Pharmacotherapy, vol. 24, pp. 1099-1104, 2004.
  2. Robert T. O'Neill et al (2010) “Statistical considerations in evaluating pharmacogenomics-based clinical effect for confirmatory trials”SAGE Journals Volume: 7 issue: 5, page(s): 525-536.
  3. Y. Ji, H. Ying, P. Dews, M.S. Farber, A. Mansour, J. Tran, R.E. Miller, and R.M. Massanari, “A Fuzzy Recognition-Primed Decision Model-Based Causal Association Mining Algorithm for Detecting Adverse Drug Reactions in Postmarketing Surveillance,” Proc. IEEE Int’l Conf. Fuzzy Systems, 2010.
  4. Christopher C Yang, Haodong Yang, Ling Jiang, Mi Zhang, Social media mining for drug safety signal detectionProceedings of the 2012 international workshop on Smart health and wellbeing 2012/10/29 PP 33-40
  5. G Niklas Norén, I Ralph Edwards, Modern methods of pharmacovigilance: detecting adverse effects of drugs, CME Clinical pharmacology Clinical Medicine 2009, Vol 9, No 5: 486–9
  6. L. Szathmary, A. Napoli, and P. Valtchev, “Towards Rare Itemset Mining,” Proc IEEE 19th Int’l Conf. Tools with Artificial Intelligence, 2007.
  7. I.R. Edwards and J.K. Aronson, “Adverse Drug Reactions: Definitions, Diagnosis, and Management,” Lancet, vol. 356, pp. 1255-1259, 2000.

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Published

2016-09-30

Issue

Section

Research Articles

How to Cite

[1]
M. Robinson Joel, Gandhi Jabakuma, W. Mercy, " Comparison Analysis on Medical Data Mining for Drug Suggestion, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 5, pp.567-570, September-October-2016. Available at doi : https://doi.org/10.32628/IJSRSET196157