International Journal of Information Engineering and Electronic Business (IJIEEB)
IJIEEB Vol. 11, No. 4, 8 Jul. 2019
Cover page and Table of Contents: PDF (size: 994KB)
New Approach to Medical Diagnosis Using Artificial Neural Network and Decision Tree Algorithm: Application to Dental Diseases
Full Text (PDF, 994KB), PP.52-60
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Author(s)
Ayedh abdulaziz Mohsen
1,*
Muneer Alsurori
1
Buthiena Aldobai
1
Index Terms
Decision Tree, Diseases, Application, Dental, Neural network, Symptoms, diagnosis.
Abstract
In this article some modern techniques have been used to diagnose the oral and dental diseases. The symptoms and causes of such disease has been studied that may cases many other serious diseases .Many cases have been reviewed through patients' records, and investigation on such causes of oral and dental disease have been carried out to help design a system that helps diagnose oral and classify them, and that system was made according to the decision tree, (Id3 and J48) and artificial neural network techniques. Sample of oral and dental diseases were collected with their symptoms to become a data base so as to help construct a diagnostic system. The graphical interface were formed in C# to facilitate the use's diagnosis process where the patient chooses the symptoms through the interface which he suffered from ,and they are analyzed using the classification techniques and then re diagnosed the disease for the user.
Cite This Paper
Ayedh abdulaziz Mohsen, Muneer Alsurori, Buthiena Aldobai, Gamil Abdulaziz Mohsen, " New Approach to Medical Diagnosis Using Artificial Neural Network and Decision Tree Algorithm: Application to Dental Diseases", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.11, No.4, pp. 52-60, 2019. DOI:10.5815/ijieeb.2019.04.06
Reference
[1]Jenny Abanto Thiago S. Carvalho Fausto M. Mendes Marcia T. Wanderley Marcelo Bönecker Daniela P. Raggio, Impact of oral diseases and disorders on oral health‐related quality of life of preschool children, Volume39, Issue2,April 2011,Pages 105-114.
[2]Iain Pretty, Michaela Goodwin, Digital Technologies in Oral & Dental Research, Volume 74, Supplement 1, Pages S1-S50 (July 2018).
[3]R. Thanigaivel, and K. R. Kumar, "Boosted Apriori: An Effective Data Mining Association Rules for Heart Disease Prediction System," Middle-East Journal of scientific Research, vol. 24, pp. 192-200, 2016.
[4]J. Banupria, and S. Kiruthika, " Heart disease using Data Mining Algorithm on Neural Network and Genetic Algorithm," International Journal of Advanced Research in Computer Science and Software Engineering, vol. 6, Issue 8, pp.40-42, 2016.
[5]C. Sowmuiya, and P. Sumitra, "Comparative Study of Predicting Heart Disease by Means of Data Mining," International Journal of Engineering and Computer Science, vol. 5 , Issue 12, pp. 19580-19582, 2016.
[6]Swathi P, Yogish H.K, Sreeraj R, “Predictive Data Mining Procedures for the Prediction of Coronory Artery disease” , IJETAE Volume 5, Issue 2 February 2015.
[7]K.Sudhakar, Dr. M. Manimekalai, “Study of Heart Disease Prediction using Data Mining” , International Journal of Advanced Research in Computer Science and Software Engineering, Volume 4, Issue 1, January 2014
[8]M. Abdar et al., "Comparing Performance of Data Mining Algorithms in Prediction Heart Diseases, "International Journal of Electrical and Computer Enginnering (IJECE), vol. 5, no. 6, 2015.
[9]Boshra Bahrami, Mirsaeid Hosseini Shirvani, “Prediction and Diagnosis of Heart Disease by Data Mining Techniques”, Journal of Multidisciplinary Engineering Science and Technology (JMEST), ISSN: 3159-0040, Vol. 2 Issue 2, February - 2015
[10]Cabena, P., Hadjinian, P., Stadler, R., Verhees, J. and Zanasi, A."Discovering data mining: From concept to implementation,".New Jersey: Prentice Hall, 1997.
[11]Chang, C.-L., and ChenC.-H."Applying decision tree and neural network to increase quality of dermatologic diagnosis," Expert Systems with Applications, 4035-4041.,2009.
[12]Chau, M., Shin,D., “A Comparative study of Medical Data classification Methods Based on Decision Tree and Bagging algorithms”, Proceedings of IEEE International Conference on Dependable,Autonomic and Secure Computing, 2009, pp.183-187.
[13]Ture, M., Kurt, I., Kurum, A. T., and Ozdamar, K,"Comparing classification techniques for predicting essential hypertension,".Expert Systems with Applications, 2005.
[14]Eom, J.-H., Kim, S.-C., and Zhang, B.-T. "AptaCDSS-E: A classifier ensemble based clinical decision support system for cardiovascular disease level prediction," Expert Systems with Applications, 2008.
[15]Vikas Chaurasia, Saurabh Pal, “Data Mining Approach to Detect Heart Diesease”, International Journal of Advanced Computer Science and Information Technology (IJACSIT) Vol. 2, No. 4, 2013, Page: 56-66, ISSN: 2296-1739
[16]Aqueel Ahmed, Shaikh Abdul Hannan, “Data Mining Techniques to Find Out Heart Diseases: An Overview”, International Journal of Innovative Technology and Exploring Engineering (IJITEE), ISSN: 2278-3075, Volume-1, Issue-4, September 2012
[17]Nidhi Bhatla, Kiran Jyoti, “An Analysis of Heart Disease Prediction using Different Data Mining Techniques”, International Journal of Engineering Research & Technology (IJERT) Vol. 1 Issue 8,October - 2012 ISSN: 2278-0181
[18]Jenn-LongLiu, Yu-Tzu, Chih-Lung Hung, "Development of evolutionary data mining algorithm and their applications to cardiac disease diagnosis", World congress on computational intelligence, 2012.
[19]Dr. Neeraj Bhargava, Girja Sharma-Dr. Ritu Bhargava-Manish Mathuria- Research Paper-Decision Tree Analysis on J48 Algorithm for Data Mining-International Journal of Advanced Research in Computer Science and Software- Engineering Page | 111 4 Volume 3, Issue 6, June 2013ISSN: 2277 128X
[20]Ankita Dewan, Meghna Sharma, ―Prediction of Heart Disease Using a Hybrid Technique in Data Mining Classification‖, ITM University Gurgaon, INDIA,2015,PP 704-706.
[21]Sivagowry .S1, Dr. Durairaj. M2 and Persia.A3 1 and 3 Research Scholar, 2 Assistant Professor,‖An Empirical Study on applying Data Mining Techniques for the Analysis and Prediction of Heart Disease ‖, Journal of School of Computer Science and Engg.Bharathidasan University, Trichy, Tamilnadu, India.
[22]Usha. K Dr, Analysis of Heart Disease Dataset using Neural network approach, IJDKP, Vol 1(5), Sep 2011.
[23]M.Akhil jabbar* B.L Deekshatulua Priti Chandra b,‖Classification of Heart Disease Using K- Nearest Neighbor and Genetic Algorithm‖, International Conference on Computational Intelligence: Modeling Techniques and Applications (CIMTA) 2013, pp 85 -94.
[24]Chaitrali S. Dangare , Sulabha S. Apte,PhD. ,‖Improved Study of Heart Disease Prediction System using Data Mining Classification Techniques‖ ,International Journal of Computer Applications (0975 888) Volume 47 No.10, June 2012.
[25]Jiawei Han and Micheline Kamber, “Data Mining Concepts and Techniques”, second edition, Morgan Kaufmann Publishers an imprint of Elsevier.
[26]V.Karthikeyani,”Comparative of Data Mining Classification Algorithm (CDMCA) in Diabetes Disease Prediction” International Journal of Computer Applications (0975 – 8887) Volume 60– No.12, December 2012.
[27]M. Anbarasi “Enhanced Prediction of Heart Disease with Feature Subset Selection using Genetic Algorithm” International Journal of Engineering Science and Technology Vol. 2(10), 2010, 5370-5376.
[28]Wei Peng, Juhua Chen and Haiping Zhou ,An Implementation of ID3 --- Decision Tree Learning Algorithm- Project of Comp 9417: Machine Learning University of New South Wales, School of Computer Science & Engineering, Sydney, NSW 2032, Australia weipengtiger@hotmail.com- page(3)
[29]Prachi Paliwal, Mahesh Malviya, “An Efficient Method for Predicting Heart Disease Problem Using Fitness Value”, (IJCSIT)
[30]http://data-mining.business-intelligence.uoc.edu/home/j48-decision-tree Website - Jordi Gironis Lecturer in Business Intelligence Master /Feel free to email at:jgironesr@uoc.edu
[31]WEKA://http://www.cs.Waikato.ac.nz/mc/weka/index.html.
[32]Weekly magazine at https://www.webteb.com/dental-health/diseases-2011-2017
[33]A scientific article from the website : https: //informatic-ar.com/id3_algorithm/-10 October 2013.
[34]CSE5230 Tutorial: The ID3 Decision Tree Algorithm. Monash University, Semester 2, 2004. Retrieved April 10, 2012, from http://www.csse.monash.edu.au/courseware/cse5230/2004/assets/decisiontreesTute.pdf.