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International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed,Open Access and Multidisciplinary

ISSN(Online):2349-7084                 Submit Paper    Check Paper Status    Conference Proposal

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Prediction of dengue with the use of AI and Data mining: An Expert system


Background/Objectives: Dengue fever is a mosquito-borne tropical disease caused by the dengue virus. It is a life-threatening disease lots of people died due to dengue because its symptoms are not detected at early stages many parsons thought that it was a normal fever or headache so that they ignore it which cause there are in dangerous situations and worst case they lose their life. Methods/Statistical analysis: We applied data mining techniques along with artificial intelligence technique to create an expert system which can diagnose dengue with the help of symptoms provided by the users. In data mining portion, we use data filtering, data cleaning and clustering, and some other technique to enhance our dataset. Moreover, in AI portion we create an expert system where we create a knowledge base, fact base and GUI portion through user enter their symptoms and our system work is to predict dengue based on symptoms that user feed in GUI as input. Findings: With the implementation of this project, we expect that our expert system is capable of predicting dengue based on person symptom's that we take as a Dataset and saves lots of life of various persons. The main aim of this project is accuracy measure and efficiency also because there is lots of work is pending in this area, and some researchers are searching for new methods. Improvements/Applications: our proposed work will apply in the field of the medical area where a person is capable of checking their dengue symptoms and analyzing their disease.

DINESH CHANDRA,SHAZIYA ISLAM,DEEPAK PANDEY."Prediction of dengue with the use of AI and Data mining: An Expert system". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.6, Issue 09,pp.340-346, September - 2019, URL :,

Keywords : Dengue, Malaria, Data Mining, Machine Learning, Artificial Intelligence, Expert System

[1]	Md Younis Md Alzarrous and Mr. surya prakash mishra, "A novel data mining techniuque to discover pattern from huge text corpous," international jounral of Modern Engineering Research, vol. 4, no. 5, p. 6, may 2014.
[2]	kashish, Anis, Shadma, Alam, Mansaf Ara Shakil, "Dengue Disease prediction Using Weka Data Mining tool," Elsevier, p. 26, Feb 2015.
[3]	Dr. Dinesh singh, "An Empirical study of Techniques and Various Domains in Data Mining for Efficient approach in Various Fields," International Jounral of New Inventions in Engineering and Technology , vol. 8, no. 1, p. 7, April 2018.
[4]	S. Chadsuthi2, K. Jampachaisri3, K. Kesorn* P. Siriyasatien1, "Dengue Epidemics Prediction: A Survey of the state of the art based on data science process," ieee, vol. 20, p. 36, october 2018.
[5]	Nopember Surabaya, Mohammad Isa Irawan n Abdul Mahatir Najar, "Extreme Learning Machine Method for Dengue Hemorrhagic Fever Outbreak Risk Level Predictio," ieee, vol. 4, p. 5, sep 2018.
[6]	Marco A. Ferreira Bircky and Ricardo Matsumura Araujoz Virginia Ortiz Andersson, "Towards Predicting Dengue Fever Rates Using Convolutional Neural Networks and Street-Level Images ," ieee, p. 8, June 2018.
[7]	Ria Arafiyah1 and Fariani Hermin1, "Data mining for dengue hemorrhagic fever (DHF) prediction with naive Bayes method," Jounral of Physics, p. 5, July 2018.
[8]	Mrs. A.Sumathi [2] P. Sathya [1], "Predicting Dengue Fever Using Data Mining Techniques," IJCST, vol. 6, no. 2, p. 3, March-April3 2018.
[9]	F. Ibrahim proposed H. Abdul Rahiml, "A NOVEL PREDICTION SYSTEM IN DENGUE FEVER USING NARMAX MODEL ," Ieee, p. 5, october 2017.
[10]	Dr.A.Anitha proposed Ms.S.Freeda Jebamalar, "A Survey on Prediction of Dengue Fever Using Data Mining Techniques," IJSEM, vol. 2, no. 12, p. 3, Dec 2017.
[11]	Dr. P. Isakki Devi P. Manivannan, "Dengue Fever Prediction Using K-Means Clustering Algorithm," Ieee, p. 5, Sep. 2017.

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