Review

Artificial intelligence in corneal topography

Volume: 2 Number: 1 January 1, 2019
EN

Artificial intelligence in corneal topography

Abstract

The purpose of this paper is to explore the effectiveness and efficiency of various artificial intelligence (AI) techniques in extracting features from corneal topographies. A considerable number of dated and contemporary related research papers have been reviewed. The author has only checked the studies that considered developing at least one AI-based algorithm for data classification of topographic patterns. The results of this review emphasize the effectiveness and efficiency of machine learning algorithms in the clinical diagnosis of various eye refractive problems.

Keywords

References

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  5. de Carvalho, L. A., & Barbosa, M. S. (2008). Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison. Arquivos Brasileiros de Oftalmologia, 71(3), 337–341. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/18641817
  6. Kabari, L., & Nwachukwu, E. (2012). Neural Networks and Decision Trees For Eye Diseases Diagnosis. In P. Vizureanu (Ed.), Advances in Expert Systems. InTech.
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Details

Primary Language

English

Subjects

Computer Software

Journal Section

Review

Authors

Nebras Hussein This is me
Iraq

Publication Date

January 1, 2019

Submission Date

August 31, 2018

Acceptance Date

November 19, 2018

Published in Issue

Year 2019 Volume: 2 Number: 1

APA
Saleh, N., & Hussein, N. (2019). Artificial intelligence in corneal topography. Journal of Intelligent Systems: Theory and Applications, 2(1), 1-6. https://doi.org/10.38016/jista.456592
AMA
1.Saleh N, Hussein N. Artificial intelligence in corneal topography. JISTA. 2019;2(1):1-6. doi:10.38016/jista.456592
Chicago
Saleh, Nazar, and Nebras Hussein. 2019. “Artificial Intelligence in Corneal Topography”. Journal of Intelligent Systems: Theory and Applications 2 (1): 1-6. https://doi.org/10.38016/jista.456592.
EndNote
Saleh N, Hussein N (January 1, 2019) Artificial intelligence in corneal topography. Journal of Intelligent Systems: Theory and Applications 2 1 1–6.
IEEE
[1]N. Saleh and N. Hussein, “Artificial intelligence in corneal topography”, JISTA, vol. 2, no. 1, pp. 1–6, Jan. 2019, doi: 10.38016/jista.456592.
ISNAD
Saleh, Nazar - Hussein, Nebras. “Artificial Intelligence in Corneal Topography”. Journal of Intelligent Systems: Theory and Applications 2/1 (January 1, 2019): 1-6. https://doi.org/10.38016/jista.456592.
JAMA
1.Saleh N, Hussein N. Artificial intelligence in corneal topography. JISTA. 2019;2:1–6.
MLA
Saleh, Nazar, and Nebras Hussein. “Artificial Intelligence in Corneal Topography”. Journal of Intelligent Systems: Theory and Applications, vol. 2, no. 1, Jan. 2019, pp. 1-6, doi:10.38016/jista.456592.
Vancouver
1.Nazar Saleh, Nebras Hussein. Artificial intelligence in corneal topography. JISTA. 2019 Jan. 1;2(1):1-6. doi:10.38016/jista.456592

Journal of Intelligent Systems: Theory and Applications