EN
Anemia Diagnosis By Using Artificial Neural Networks
Abstract
In the last years, applications of artificial intelligence for diagnosis of diseases as a decision support system has been widely used. In these applications, the state that if the patient contracts to the suspected is classified as positive or negative. Although in the previous works which use artificial neural networks various diseases especially some cancer types have been studied, anemia has remained as an disease that has not been focused. Anemia which can emerge due to the degeneration of blood structure, blood loss or elimination of erythrocytes is a disease that is widely encountered and can result in significant health problems. In this study, a decision support system using artificial neural network has been proposed for the diagnosis of anemia according to the selected comprehensive blood laboratory test.
Keywords
Supporting Institution
Yücelen Grup
Thanks
Dr. Ali Yücelen
References
- [1] M. Behnam, A. Mohammadhossein, C. Shing, “A medical decision support system for disease diagnosis under uncertainty”, Expert Systems With Applications 88, 2017.
- [2] J. Jingchi, L. Xueli, Z. Chao, G. Yi, Y. Qiubin, “Learning and inference in knowledge-based probabilistic model for medical diagnosis”, Knowledge-Based Systems, 2017.
- [3] J. Amin, M. Mohammad, “Fuzzy Evidential Network and Its Application as Medical Prognosis and Diagnosis Models”, Journal of Biomedical Informatics, 2017.
- [4] S. Gandhi, C. Edgar, L. Jose, E. Marisol, R. Alejandro, P. Yuliana, “Collective intelligence in medical diagnosis systems: A case study”, Computers in Biology and Medicine, 2016.
- [5] R. Alejandro, A. Giner, “An approach for solving multi-level diagnosis in high sensitivity medical diagnosis systems through the application of semantic Technologies”, Computers in Biology and Medicine 43, 2013. [6] E. McLean, M. Cogswell, I. Egli, D. Wojdyla, B. Benoist, “Worldwide prevalence ofanaemia, who vitamin and mineral nutrition information system”, Public Health Nutr.”, 2009.
- [7] I. Anand, J. McMurray, J. Whitmore, M. Warren, A. Pham, A. McCamish, P. Burton, “Anemia and its relationship to clinical outcome in heart failure”, Circulation, 2004.
- [8] H. Erdem, A. Berkol, M. Sert, “Comparative Study of Universal Function Approximators (Neural Network, Fuzzy Logic, ANFIS) for Non-Linear Systems” International Journal of Scientific Research in Information Systems and Engineering (IJSRISE) 2015.
- [9] O. Unal, A. Berkol, E. Tartan, “Using Artificial Intelligence Based Expert System for Selection of Design Subcontractors: A Case Study in Aerospace Industry”, 8th IEEE International Conference on Mechanical and Aerospace Engineering (ICMAE 2017).
Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Publication Date
July 31, 2020
Submission Date
January 28, 2020
Acceptance Date
July 9, 2020
Published in Issue
Year 2020 Volume: 4 Number: 1
APA
Berkol, A., Tartan, E., & Ekici, Y. (2020). Anemia Diagnosis By Using Artificial Neural Networks. International Journal of Multidisciplinary Studies and Innovative Technologies, 4(1), 14-17. https://izlik.org/JA49SG47HB
AMA
1.Berkol A, Tartan E, Ekici Y. Anemia Diagnosis By Using Artificial Neural Networks. IJMSIT. 2020;4(1):14-17. https://izlik.org/JA49SG47HB
Chicago
Berkol, Ali, Emre Tartan, and Yahya Ekici. 2020. “Anemia Diagnosis By Using Artificial Neural Networks”. International Journal of Multidisciplinary Studies and Innovative Technologies 4 (1): 14-17. https://izlik.org/JA49SG47HB.
EndNote
Berkol A, Tartan E, Ekici Y (July 1, 2020) Anemia Diagnosis By Using Artificial Neural Networks. International Journal of Multidisciplinary Studies and Innovative Technologies 4 1 14–17.
IEEE
[1]A. Berkol, E. Tartan, and Y. Ekici, “Anemia Diagnosis By Using Artificial Neural Networks”, IJMSIT, vol. 4, no. 1, pp. 14–17, July 2020, [Online]. Available: https://izlik.org/JA49SG47HB
ISNAD
Berkol, Ali - Tartan, Emre - Ekici, Yahya. “Anemia Diagnosis By Using Artificial Neural Networks”. International Journal of Multidisciplinary Studies and Innovative Technologies 4/1 (July 1, 2020): 14-17. https://izlik.org/JA49SG47HB.
JAMA
1.Berkol A, Tartan E, Ekici Y. Anemia Diagnosis By Using Artificial Neural Networks. IJMSIT. 2020;4:14–17.
MLA
Berkol, Ali, et al. “Anemia Diagnosis By Using Artificial Neural Networks”. International Journal of Multidisciplinary Studies and Innovative Technologies, vol. 4, no. 1, July 2020, pp. 14-17, https://izlik.org/JA49SG47HB.
Vancouver
1.Ali Berkol, Emre Tartan, Yahya Ekici. Anemia Diagnosis By Using Artificial Neural Networks. IJMSIT [Internet]. 2020 Jul. 1;4(1):14-7. Available from: https://izlik.org/JA49SG47HB