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Issue:Intuitionistic fuzzy generalized net model of adolescent idiopathic scoliosis classification and the curve progression probability

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Title of paper: Intuitionistic fuzzy generalized net model of adolescent idiopathic scoliosis classification and the curve progression probability
Author(s):
Simeon Ribagin
Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev str., bl. 105, 1113 Sofia, Bulgaria
sim_ribagin@mail.bg
Peter Vassilev
Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev str., bl. 105, 1113 Sofia, Bulgaria
peter.vassilev@gmail.com
Tania Pencheva
Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev str., bl. 105, 1113 Sofia, Bulgaria
tania.pencheva@biomed.bas.bg
Sławomir Zadrożny
Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland
Slawomir.Zadrozny@ibspan.waw.pl
Published in: "Notes on Intuitionistic Fuzzy Sets", Volume 23, 2017, Number 3, pages 88—95
Download:  PDF (157 Kb  Kb, File info)
Abstract: By far the most common type of scoliosis in the adolescent period is one in which the cause is not known and is called idiopathic or adolescent idiopathic scoliosis (AIS). The objective of the present work is to propose a novel approach for classification and evaluation of the curve progression probability in patients with confirmed AIS, using the apparatus of Generalized Nets (GN) Theory and the Intuitionistic fuzzy sets (IFS).
Keywords: Intuitionistic fuzzy generalized net model, Adolescent idiopathic scoliosis.
AMS Classification: 68Q85, 03E72.
References:
  1. Atanassov, K. (1991) Generalized Nets. World Scientific, Singapore.
  2. Atanassov, K. (2007) On Generalized Nets Theory. Prof. M. Drinov Academic Publishing House, Sofia.
  3. Atanassov K., Mavrov, D., & Atanassova, V. (2014) Intercriteria decision making: A new approach for multicriteria decision making, based on index matrices and intuitionistic fuzzy sets, Issues in Intuitionistic Fuzzy Sets and Generalized Nets, 11, 1–8.
  4. Cobb, J. R. (1948) Outline for the Study of Scoliosis. AAOS Instr. Course Lect., 5, 261–275.
  5. King, H. A., Moe, J. H., Bradford, D. S., & Winter, R. B. (1983) The Selection of Fusion Levels in Thoracic Idiopathic Scoliosis. J. Bone Joint Surg. Am., 65, 1302–1313.
  6. Ribagin, S., Atanassov, K., Roeva O., & Pencheva, T. (2016) generalized net model of adolescent idiopathic scoliosis diagnosing, In: Uncertainty and Imprecision in Decision Making and Decision Support: Cross Fertilization, New Models and Applications, Springer-Verlag, 2016 (in press).
  7. Risser, J. C. (1958) The Iliac Apophysis: An Invaluable Sign in the Management of Scoliosis. Clin. Orthop. 11, 111–119.
  8. Todinova, S., Mavrov, D., Krumova, S., Marinov, P., Atanassova, V., Atanassov, K., & Taneva, S. G. (2016) Blood plasma thermograms dataset analysis by means of intercriteria and correlation analyses for the case of colorectal cancer, Int J Bioautomation, 20(1), 115–124.
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