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An Intelligent Knowledge-based Approach for the Management of Human Immunodeficiency Virus and Tuberculosis
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 115 - Number 2 |
| Year of Publication: 2015 |
| Authors: Djam Xaveria Youh |
10.5120/20124-2198
|
Djam Xaveria Youh . An Intelligent Knowledge-based Approach for the Management of Human Immunodeficiency Virus and Tuberculosis. International Journal of Computer Applications. 115, 2 ( April 2015), 30-37. DOI=10.5120/20124-2198
Abstract
Dealing with Human Immunodeficiency Virus (HIV) and Tuberculosis (TB) as co-infection is not easy. Stigmatization, rejection and discrimination of TB and HIV patients have become the major challenges in medical field which makes it very difficult for the health care professionals to communicate with their patients. The inherent complexities of medical practices make traditional approaches of diagnosis and predicting treatment outcome inappropriate. There is the need for the provision of a system to mitigate these effects. Till date, the research done on Fuzzy Cognitive Maps have not been able to effectively handle missing data in order to predict the patient health status in spite of many existing methods of dealing with missing data. In this paper, a new diagnostics predictive algorithm of fuzzy cognitive map was developed to improve the efficiency of the prediction of patient health status in case of HIV or TB. The system is an advancement of that proposed by Djam and Kimbi in 2011, with an additional factors on effective prediction measures. The diagnosis and treatment processes were modeled based on Domain Experts' judgments. The approach proposed in this paper was validated using real patient data and the experimental results of the research show that the new proposed algorithm can effectively simulate the behavior of a medical expert and was successfully employed in designing computer-based diagnostic predictive models for effective patient management.
References
- P. D. O. Davies, "The Role of DOTS in Tuberculosis Treatment and Control," America Journal of Respiratory and Critical Care Medicine, vol. 3, pp. 203-209, 2003.
- X. Y. Djam and Y. H. Kimbi, "A Decision Support System for Tuberculosis Diagnosis," Pacific Journal of Science and Technology, vol. 2, pp. 410-425, 2011.
- J. Greenhalgh, R. Flynn, A. F. Long, and S. Tyson, "Tacit and Encoded Knowledge in the Use of Standardized Outcome Measures in Multidisciplinary Team Decision Making: A Case Study of In-patient Neurorehabilitation. Social Science & Medicine, 67(1):183-194, 2008.
- A. D. Harries and C. Dye, "Tuberculosis (Centennial Review). Annals of Tropical Medicine and Parasitology, vol. 100, pp. 415-431, 2006.
- B. Kosko, "Fuzzy Cognitive Maps," International Journal of Man-Machine Studies, vol. 24, pp. 65-75, 1986.
- E. I. Papageorgiou, C. D. Stylios, and P. P. Groumpos, "An integrated two-Level Hierarchical Decision Making System Based on Fuzzy Cognitive Maps (Fcms)," IEEE Transactions on Biomedical Engineering, vol. 50, pp. 1326–1339, 2003.
- E. I. Papageorgiou, P. Spyridonos, P. Ravazoula, P. P. Groumpos, and G. Nikiforidis, "A soft computing method for tumour grading cognitive maps, Journal of Artificial Intelligence in Medicine, vol. 36, 58–70, 2006.
- E. I. Papageorgiou, C. D. Stylios, and P. P. Groumpos, "Novel Architecture for Supporting Medical Decision Making of Different Data Types Based on Fuzzy Cognitive Map Framework," In Proc. o f 29th IEEE EMBS Annual International Conference in Medicine and Biology Society, Lyon, France, 21-23, 2007.
- E. I. Papageorgiou, P. Spyridonos, D. Glotsos, C. D. Stylios, P. Ravazoula, G. Nikiforidis, and P. P. Groumpos,"Brain Tumour Characterization Using Soft Computing of Fuzzy Cognitive Maps. " Applied Soft Computing, vol. 8. PP. 820-828, 2008
- C. D. Stylios, V. C. Georgopoulos and P. P. Groumpos, "The Use of Fuzzy Cognitive Maps in Modeling Systems," Studies in Fuzziness and Soft Computing, vol. 5, pp. 18-30, 2011.
- C. D. Stylios and V. C. Georgopoulos, "Medical Decision Support Systems based on Soft Computing techniques," Preprints of the 18th IFAC World Congress Milano (Italy), pp. 14115-14120. August 2011.
- World Health Organization (2006). The Stop TB Strategy Document, WHO/HTM/TB, Geneva:WHO.
- L. A. Zadeh, "Fuzzy sets. Info. Control," vol. 3, pp. 338-353, 1965a.
- L. A. Zadeh, "Fuzzy sets and Systems. In Proc. of International Symposium on System Theory," Polytechnic Institute of Brooklyn, pp. 234-241, 1965b.
- L. A. Zadeh, Biological applications of the theory of fuzzy set and systems, In Proc. of International Symposium on Biocybernetics of the Central Nervous System (Little, Brown and Company, Boston), pp. 199-206, 1969.
- M. Musen, Y. Shahar, and E. Shortliffe, E. "Clinical decision support systems," In: E. Shortliffe, L. Perreault, eds. Medical Informatics: Computer Applications in Health Care and Biomedicine. New York, NY: Springer-Verlag New York, Inc; 573–609, 2001.
- J. W. Grzymala-Busse and M. Hu, "A comparison of several approaches to missing attribute values in data mining," Rough Sets Current Trends Comput, pp. 378–385, 2000.
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