An Efficient Decision based Classification Model for Medical Diagnosis

  IJCOT-book-cover
 
International Journal of Computer & Organization Trends  (IJCOT)          
 
© 2019 by IJCOT Journal
Volume - 9 Issue - 2
Year of Publication : 2019
Authors :  R.S.Ravindra Babu, M.Ravindra, P.Ch.Gayathri, S.Ramu, P.Nagarjuna Reddy

Citation

MLA Style:R.S.Ravindra Babu, M.Ravindra, P.Ch.Gayathri, S.Ramu, P.Nagarjuna Reddy "A Double-Registration Based Algorithm for Secure Elections" International Journal of Computer and Organization Trends 9.2 (2019): 1-4.

APA Style:R.S.Ravindra Babu, M.Ravindra, P.Ch.Gayathri, S.Ramu, P.Nagarjuna Reddy (2019). An Efficient Decision based Classification Model for Medical Diagnosis. International Journal of Computer and Organization Trends, 9(2), 1-4.

Abstract

We propose an efficient knowledge expert system based supervised model for classification of medical entities. Decision expert system helps the classification during the classification if any attribute missed during the computation of probability. Classification model analyzes the testing sample by forwarding to training sample.Decision-making statements can gives the analysis over the samples of training dataset, but cannot compute the missing values. Classification Model computes the initial probability, conditional probability and posterior probability and to analyze the testing medical diagnosis sample. Our proposed model gives more efficient results than traditional models.

References

[1] Cognitive impairment assessed at annual geriatric health examinations predicts mortality among the elderly,? Preventive Medicine, byC. Y. Wu, Y. C. Chou, N. Huang, Y. J. Chou, H. Y. Hu, and C. P. Li,.
[2] An Efficient TCM Supervised Learning Approach With Naïve Bayesian Classifier? byNaveen Gosu , VakacharlaDurgaprasadarao , N. Tulasi Radha
[3] Health checks for the over-65s,? http://www.nhs.uk/Livewell/
[4] General health checks in adults for reducing morbidity and mortality from disease ( Review ),? by L. Krogsbøll, K. Jørgensen, C. Grønhøj Larsen, and P. Gøtzsche
[5] A relative similarity based method for interactive patient risk prediction,? by B. Qian, X. Wang, N. Cao, H. Li, and Y.-G. Jiang
[6] Ranking-based classification of heterogeneous information networks,? by M. Ji, J. Han, and M. Danilevsky,
[7] A general graph-based semi-supervised learning with novel class discovery,? Neural Comput. Appl., vol. 19, pp. 549–555, 2010. By F. Nie, S. Xiang, Y. Liu, and C. Zhang,
[8] Compact graph based semi-supervised learning for medical diagnosis in alzheimer‘s disease,? by M. Zhao, R. H. M. Chan, T. W. S. Chow, and P. Tang,
[9] Mining Health Examination Records—A Graph-Based Approach? by Ling Chen, Xue Li, Member, IEEE, Quan Z. Sheng, Member, IEEE, Wen-Chih Peng, Member, IEEE, John Bennett, Hsiao-Yun Hu, and Nicole Huang,
[10] Genome-wide inferring gene-phenotype relationship by walking on the heterogeneous network,? by Y. Li and J. C. Patra

Keywords
computation, Medical Diagnosis, ICD