A Method for Prognosis of Primary Open-Angle Glaucoma


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Abstract


A method for prognosis of primary open-angle glaucoma (POAG) using the mathematical apparatus of Markov processes is developed in the article. The mathematical apparatus of Markov processes with discrete states and discrete time was used to describe the course of glaucoma. According to the clinical approbation of the proposed method, the prognosis was made unmistakably in 16 surveyed patients. Prognosis was confirmed in 82% of cases. The proposed method increases the prognosis of POAG development significantly. The introduction of this method for POAG prognosis in ophthalmology practice allows improving the quality level of medical service for patients.
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Keywords


Duration; Markov Chain; Primary Open-Angle Glaucoma; Probability; Prognosis

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References


P.N. Baird Myocilin mutations and their role in open-angle glaucoma, In: J. Tombran-Tink, C.J. Barnstable, M.B. Shields (eds), Mechanisms of the glaucomas: disease processes and therapeutic modalities, Humana Press, pp 205-217, Totowa, NJ, 2008.

U.R. Acharya, O. Faust, Z. Kuanyi, TMX Irene, B. Maggie,

S. Dua et al. Automatic diagnosis of glaucoma using digital fundus images, In: S. Dua, U.R. Acharya, EYK Ng (eds), Computational analysis of the human eye with applications, World Scientific Publishing, pp 207-226, Singapore, 2011.

M.G. McMenemy Primary open angle glaucoma, In:

PN. Schacknow, J.R. Samples (eds), The glaucoma book: A practical, evidence-based approach to patient care, Springer,

pp 399-419, New York, 2010.

Eye Ris Vision Center. Glaucoma. Available at http://www.eyerisvision.com/glaucoma.html. Accessed 4 February 2013.

A. Wright Common forms of visual handicap, In: A. Wright,

N. Hastie (eds), Genes and common diseases: genetics in modern medicine, Cambridge University Press, pp 488-504, Cambridge, 2007.

S. Hayakawa, N. Hamajima, T. Yamamoto, Y. Kitazawa Analysis of therapeutic prognosis of primary open-angle glaucoma by the proportional hazards model and the life-table method. Nihon Ganka Gakkai Zasshi, Vol 98: 379-384, 1994.

G.S. Ang, T. Eke Lifetime visual prognosis for patients with primary open-angle glaucoma, Eye, Vol. 21: 604-608, 2007.

T.S. Kim Prognosis of the clinical course of primary open-angle glaucoma with help of artificial neural networks, Glaucoma, Vol: 1: 7-10, 2007.

T.S. Kim, E.N. Komarovsky Prognosis of the clinical course of primary open-angle glaucoma with help of artificial neural networks, Advances in Ophthalmology: Conference Proceedings; p 226, Moscow, Russian Federation, 26-27 Sept 2003.

A.P. Nesterov Glaucoma Medicina Publishing House (Moscow, 1995).

V.V. Egorov, I.L. Bachaldin, E.L. Sorokin, inventors; "Eye Microsurgery" State Intersectoral Research and Technology Complex, assignee. Method for diagnosis of glaucoma, Russian Federation patent 2187983; IPC A61F9/00, A61B3/10. 27 Aug 2002.

V.V. Egorov, G.P. Smolyakova, T.V. Borisova, inventors; "Eye Microsurgery" State Intersectoral Research and Technology Complex, assignee. Method for prognosing the development of primary glaucoma after normalization of intraocular pressure, Russian Federation patent 2346644; IPC A61B3/10, A61B5/053. 20 Feb 2009.

S.A. Klyuev Modeling in natural science (Slavyansk-na-Kubani; 2009).

A.N. Strashnenko, E.V. Vysotskaya Mathematical model of sequences of therapeutic and diagnostic measures in primary open-angle glaucoma, New information technologies in scientific research and education: Conference Proceedings, pp 250-252, Ryazan, Russian Federation, 17-19 Nov 2010.

J.G. Kemeny, J.L. Snell Finite Markov chains. University series in undergraduate mathematics (Van Nostrand; 1960).

Rojathai, S., Venkatesulu, M., An effective tamil speech word recognition technique with aid of MFCC and HMM (Hidden Markov Model), (2013) International Review on Computers and Software (IRECOS), 8 (2), pp. 577-586.

Krimi, S., Ouni, K., Ellouze, N., ECG signal classification using hidden Markov tree, (2010) International Review on Computers and Software (IRECOS), 5 (6), pp. 615-619.

Mohanna, Y., Bazzi, O., Zaiour, A., Alaeddine, A., Georges, S., Slaoui, F., Environmental non-speech sound recognition using hidden markov model. case study: Glass break sounds, (2010) International Review on Computers and Software (IRECOS), 5 (2), pp. 134-144.


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