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A Survey on Medical Text Mining

by Revathi M Nair, Sindhu L.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 108 - Number 15
Year of Publication: 2014
Authors: Revathi M Nair, Sindhu L.
10.5120/18985-0423

Revathi M Nair, Sindhu L. . A Survey on Medical Text Mining. International Journal of Computer Applications. 108, 15 ( December 2014), 5-11. DOI=10.5120/18985-0423

@article{ 10.5120/18985-0423,
author = { Revathi M Nair, Sindhu L. },
title = { A Survey on Medical Text Mining },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 108 },
number = { 15 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 5-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume108/number15/18985-0423/ },
doi = { 10.5120/18985-0423 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:43:02.769369+05:30
%A Revathi M Nair
%A Sindhu L.
%T A Survey on Medical Text Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 108
%N 15
%P 5-11
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Medical diagnosis is considered as an important yet complicated task that needs to be executed accurately and efficiently. The automation of this system will be very useful for the medical field. Due to recent technology advances, large masses of medical data are available. These large data contain valuable information for diagnosing diseases. Text mining techniques are using to extract useful patterns from these mass data. It provides a user- oriented approach to the novel and hidden patterns in the data. This paper intends to provide the survey of various medical text mining techniques used in medical field. The purpose of this survey is to obtain a most suitable text mining technique for the medical data.

References
  1. Shah Neha K "Introduction of Text Mining and An Analysis of Text Mining Techniques" Paripex- Indian Journal of Research , volume :2,Issue:2,February 2013
  2. Vishal Gupta, Gurpreet S. Lehal, "A Survey of Text Mining Techniques and Applications", Journal Of Emerging Technologies In Web Intelligence, VOL. 1, NO. 1, AUGUST 2009
  3. N. Kanya and S. Geetha ,"Information Extraction: A Text Mining Approach", IET-UK International Conference on Information and Comm. Technology in Electrical Sciences, IEEE(2007), Dr. M. G. R. University, Chennai, Tamil Nadu, India,1111- 1118.
  4. Sungjick Lee and Han-joon Kim, "News Keyword Extraction for Topic Tracking", 4th International conference on Networked Computing and Advanced Information Management, IEEE (2008), Korea. 554-559.
  5. Vishal Gupta,Guruprit Lehal,"A survey of Text Summarization Extractive Techniques", Journal Of Emerging Technologies In Web Intelligence, Vol. 2, No. 3, August 2010.
  6. Jinshu, Su. , Zhang, Bofeng. , and Xin, Xu (2006). Advances in Machine Learning Based Text Categorization, Journal of Software, vol. 17, No. 9, pp1848-1859.
  7. Eui-Hong (Sam), Han George Karypis, Vipin Kumar, "Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification", Army HPC Research Center University of Minnesota.
  8. Goharian & Grossman, Data Mining Classification, Illinois Institute of Technology, http://ir. iit. edu/~nazli/cs422/CS422-Slides/DM-Classification. pdf, (2003).
  9. Ranjit Abraham, Jay B. Simha, S. Sitharama Iyengar, "Effective Discretization and Hybrid feature selection using Naïve Bayesian classifier for Medical datamining" International Journal of Computational Intelligence Research. ISSN 0974-1259 Vol. 4, No. X (2008).
  10. Periklis Andritsos, "Data Clustering Techniques", University of Toronto, March 11, 2002
  11. Prof. M. S. Prasad Babu, K. Swapna, Tilakachuri Balakrishna, Prof. N. B. Venkateswarulu, "An Implementation of Hierarchical Clustering on Indian Liver Patient Dataset", IJETCAS 14-495; © 2014,
  12. Rowena Chau, Ah Chung Tsoi, Markus Hagenbuchner, Vincent C. S. Lee, "A ConceptLink Graph for Text Structure Mining", , Wellington, New Zealand, January 2009.
  13. Yllias Chali, Shafiq R. Joty, Sadid A. Hasan, "Complex Question Answering: Unsupervised Learning Approaches and Experiments", Journal of Artificial Intelligence Research 35 (2009).
  14. Ji Hoon Kang, Dong Hoon Yang, Young Bae Park, and Seoung Bum Kim, "A Text Mining Approach to Find Patterns Associated with Diseases and Herbal Materials in Oriental Medicine", International Journal of Information and Education Technology, Vol. 2, No. 3, June 2012.
  15. H. Hu, J. Li, A. Plank, H. Wang and G. Daggard, "A Comparative Study of Classification Methods For Microarray Data Analysis", Proc. Fifth Australasian Data Mining Conference (AusDM2006), Sydney, Australia. CRPIT, ACS, vol. 61, (2006), pp. 33-37.
  16. D. Bertsimas, M. V. Bjarnadóttir, M. A. Kane, J. C. Kryder, R. Pandey, S. Vempala and G. Wang, "Algorithmic prediction of health-care costs", Oper. Res. , vol. 56, no. 6, (2008), pp. 1382-1392.
  17. C. H. Jena, C. C. Wang, B. C. Jiangc, Y. H. Chub and M. S. Chen, "Application of classification techniques on development an early-warning systemfor chronic illnesses", Expert Systems with Applications, vol. 39, (2012), pp. 8852-8858.
  18. M. Shouman, T. Turner and R. Stocker, "Applying K-Nearest Neighbour in Diagnosing Heart Disease Patients", International Conference on Knowledge Discovery (ICKD-2012), (2012).
  19. D. Y. Liu, H. L. Chen, B. Yang, X. E. Lv, N. L. Li and J. Liu, "Design of an Enhanced Fuzzy k-nearest Neighbor Classifier Based Computer Aided Diagnostic System for Thyroid Disease", Journal of Medical System, Springer, (2012).
  20. C. Chien and G. J. Pottie, "A Universal Hybrid Decision Tree Classifier Design for Human Activity Classification", 34th Annual International Conference of the IEEE EMBS San Diego, California USA, (2012) August 28-September 1.
  21. T. H. A. Soliman, A. A. Sewissy and H. A. Latif, "A Gene Selection Approach for Classifying Diseases Based on Microarray Datasets", 2nd International Conference on Computer Technology and Development (lCCTD 2010), (2010).
  22. E. Avci, "A new intelligent diagnosis system for the heart valve diseases by using genetic-SVM classifier", Expert Systems with Applications, Elsevier, vol. 36, (2009), pp. 10618-10626.
  23. O. Er, N. Yumusakc and F. Temurtas, "Chest diseases diagnosis using artificial neural networks", Expert Systems with Applications, vol. 37, (2010), pp. 7648-7655.
  24. R. Das, I. Turkoglub and A. Sengur, "Effective diagnosis of heart disease through neural networks ensembles", Expert Systems with Applications, vol. 36, (2009), pp. 7675-7680.
  25. D. I. Curiac, G. Vasile, O. Banias, C. Volosencu and A. Albu, "Bayesian Network Model for Diagnosis of Psychiatric Diseases", Proceedings of the ITI 2009 31st Int. Conf. on Information Technology Interfaces, Cavtat, Croatia, (2009) June 22-25.
  26. J. J. Tapia, E. Morett and E. E. Vallejo, "A Clustering Genetic Algorithm for Genomic Data Mining", Foundations of Computational Intelligence, vol. 4 Studies in Computational Intelligence, vol. 204, (2009), pp. 249-275.
  27. T. Balasubramanian and R. Umarani, "An Analysis on the Impact of Fluoride in Human Health (Dental) using Clustering Data mining Technique", Proceedings of the International Conference on Pattern Recognition, Informatics and Medical Engineering, (2012) March 21-23.
  28. J. Escudero, J. P. Zajicek and E. Ifeachor, "Early Detection and Characterization of Alzheimer's Disease in Clinical Scenarios Using Bioprofile Concepts and K-Means", 33rd Annual International Conference of the IEEE EMBS Boston, Massachusetts USA, (2011) August 30-September 3.
  29. H. Chipman and R. Tibshirani, "Hybrid hierarchical clustering with applications to microarray data", Biostatistics, vol. 7, no. 2, (2009), pp. 286-301.
  30. T. S. Chen, T. H. Tsai, Y. T. Chen, C. C. Lin, R. C. Chen, S. Y. Li and H. Y. Chen, "A Combined K-Means and Hierarchical Clustering Method for improving the Clustering Efficiency of Microarray", Proceedings of 2005 International Symposium on Intelligent Signal Processing and Communication Systems, (2005).
  31. M. E. Celebi, Y. A. Aslandogan and R. P. Bergstresser, "Mining Biomedical Images with Density-based Clustering", Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05), (2005).
  32. J. Yanqing, H. Ying, J. Tran, P. Dews, A. Mansour and R. Michael Massanari, "Mining Infrequent Causal Associations in Electronic Health Databases", 11th IEEE International Conference on Data Mining Workshops, (2011).
  33. S. Soni and O. P. Vyas, "Using Associative Classifiers for Predictive Analysis in Health Care Data Mining", International Journal of Computer Applications (0975 – 8887), vol. 4, no. 5, (2010) July.
Index Terms

Computer Science
Information Sciences

Keywords

Information Extraction Summarization Clustering Classification Topic Tracking Information Visualization Concept Linkage Association Rule Mining Question Answering.

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