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Reseach Article

Health Diagnosis Expert Advisory System on Trained Data Sets for Hyperthyroid

by V Prasad, T Srinivasa Rao, A Veera Reddy, B Chaitanya
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 102 - Number 3
Year of Publication: 2014
Authors: V Prasad, T Srinivasa Rao, A Veera Reddy, B Chaitanya
10.5120/17799-8611

V Prasad, T Srinivasa Rao, A Veera Reddy, B Chaitanya . Health Diagnosis Expert Advisory System on Trained Data Sets for Hyperthyroid. International Journal of Computer Applications. 102, 3 ( September 2014), 40-46. DOI=10.5120/17799-8611

@article{ 10.5120/17799-8611,
author = { V Prasad, T Srinivasa Rao, A Veera Reddy, B Chaitanya },
title = { Health Diagnosis Expert Advisory System on Trained Data Sets for Hyperthyroid },
journal = { International Journal of Computer Applications },
issue_date = { September 2014 },
volume = { 102 },
number = { 3 },
month = { September },
year = { 2014 },
issn = { 0975-8887 },
pages = { 40-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume102/number3/17799-8611/ },
doi = { 10.5120/17799-8611 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:32:12.199873+05:30
%A V Prasad
%A T Srinivasa Rao
%A A Veera Reddy
%A B Chaitanya
%T Health Diagnosis Expert Advisory System on Trained Data Sets for Hyperthyroid
%J International Journal of Computer Applications
%@ 0975-8887
%V 102
%N 3
%P 40-46
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a collection of 28 pristine symptoms which are used for the identification of Hyperthyroid disease which are heartwarming to humankind. Ghastly, Hyperthyroid affect people without being noticed until the end. In this Health Diagnose Expert Advisory System (HDEAS) we proposed a method for diagnosing the Hyperthyroid disease by enabling a list of symptoms that the person is likely to suffer from. Here the diagnosis is done by the method of prediction using Trained Data Sets(TDS) and the results are compared by using suitable Data Matching Systems (DMS). The TDS are provided by Intelligent System Laboratory of K. N. Toosi University of Technology, Imam Khomeini Hospital . Proceedings of this research showed that HDEAS can be used effectively. The acquainted knowledge is represented in the diagrams, charts and tables. The database consists of four wide classifications of Thyroid Disease, with well-organized pattern structure of symptoms. By providing an affable interface, user can input the data in the questionnaire form developed. This work predicts the actual levels of the hyperthyroid in human body.

References
  1. TDD via Hybrid Architecture Composing Rough Data Sets & ML Algorithms. , Second International Conference on Emerging Research in Computing , Information , Communication and Applications (ERCICA-2014) . , Preceding Published in ELSEVIER , Volume 1 , Issue 1 , Pages: 307-316
  2. Plug In Generator To Produce Various Output For Unique Data. , International Journal of Research in Engineering and Sciences( IJRES) , Volume 2, Issue 2, Pages :14-20
  3. Offline Analysis & Optimistic Approach on Livestock Expert Advisory System, Artificial Intelligent Systems and Machine Learning CIIT Journals , , Volume 5, Issue 12, Pages :488
  4. https://archive. ics. uci. edu/ml/datasets/Thyroid+Disease
  5. USING ARTIFICIAL NEURAL NETWORK IN DIAGNOSIS OF THYROID DISEASE: A CASE STUDY ,International Journal on Computational Sciences & Applications (IJCSA) Vol. 3, No. 4, August 2013
  6. Expert System Based on Neural-Fuzzy Rules for Thyroid Diseases Diagnosis© Springer-Verlag Berlin Heidelberg 2012
  7. Improve Computer-Aided Diagnosis with Machine Learning Techniques Using Undiagnosed Samples Ming Li and Zhi-Hua Zhou, Senior Member, IEEE ,2006
  8. Roman, W. Swiniarski, Andrzej Skowron," Rough Set Methods in Feature Selection and Recognition", Pattern Recognition Letters, vol. 24, pp. 833-849, 2003.
  9. Georg Peters, Richard Weber, Rene Nowatzke, "Dynamic Rough Clustering and its Applications", Applied Soft Computing, vol. 12, pp. 3193-3207, 2012.
  10. Pawlak, Z. , " Rough Sets- Theoretical Aspects of Reasoning about Data", Kluwer Academic, Dordrecht, 1991.
  11. Polkowski, L. , Skowron, A. (Eds), Rough Sets in Knowledge Discovery, Physica- Verlag, Heidelberg, vols: 1 and 2, 1998
  12. Sara El-Sayed El-Metwally, Elsayed Radwan, Taher Hamza, " Multiple DNA Sequence Alignment using a Hybrid Model of GA and Rough Sets", Egyptian Computer Science Journal, vol. 34 no. 3, May 2010.
  13. CROCHEMORE, CZUMAJ -Speeding up two string-matching algorithms -, et al. - 1994
  14. Thyroid Disease Diagnoses using C4. 5 Algorithms and Data Mining Techniques ,2011
  15. Keles, A. , "ESTDD: Expert System For Thyroid Diseases Diagnosis", Expert Syst. Appl. vol. 34 no. 1,pp. 242–246, 2008.
  16. Defend Data using ELGAMAL Digital Signature Data Decryption Algorithm. , (IJCSIT) International Journal of Computer Science and Information Technologies, Volume 5 , Issue 4, Pages : 5062-5067
  17. Human Motion Detection Using Passive Infra Red Sensor. , International Journal of Research in Computer Applications & Information © IASTER 2014, Volume 2, Issue 2, Pages :28-32.
Index Terms

Computer Science
Information Sciences

Keywords

Data Matching System Health Expert Advisory System Knowledge Base Prediction Trained Data Sets UCI Machine Learning Data Sets.