Abstract
In this paper, we present an improved prediction model for progression of ocular hypertension to primary open angle glaucoma using a random forest classification approach. Our model comprises two phases: risk factor calculation and prediction. We start by calculating the risk factors associated with the outcome, followed by a prediction phase that utilises a random forest approach for classification into one of four obtained classes, namely low, mid, high, and moderate. Experimental results show that the employed random forest classifier provides better prediction accuracy compared to other machine learning techniques including Bayes net, multi-layer perceptron, radial basis function and naive Bayes tree classifiers.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Distelhorst, J.S., Hughes, G.M.: Open-angle glaucoma. Am. Fam. Physician 67, 1937–1944 (2003)
Weston, B.C., Aliabadi, Z., White, G.L.: Glaucoma review for the vigilant clinician. Clinician Reviews 10, 59–74 (2000)
Fleming, C., Whitlock, E.P., Beil, T.: Screening for primary open-angle glaucoma in the primary care setting: an update for the US preventive services task force. Ann. Fam. Med. 3, 167–170 (2005)
Kroese, M., Burton, H.: Primary open angle glaucoma. The need for a consensus case definition. J. Epidemiol. Community Health 57, 752–754 (2003)
Waly, M.I., Sharawyand, A., Wahba, K.: A Comparison of Different Prediction Models in the Progression of Ocular hypertension to Primary Open Angle Glaucoma. International Journal of Applied Information Systems 5(3), 30–41 (2013)
Nduaguba, C., Lee, R.K.: Glaucoma screening: current trends, economic issues, technology, and challenge. Curr. Opin. Ophthalmol. 17, 142–152 (2006)
American Academy of Ophthalmology, Primary Open-Angle Glaucoma, Limited Revision (Preferred Practice Pattern). American Academy of Ophthalmology, San Francisco (2010), http://www.aao.org/ppp (last seen at April 20, 2014)
Severn, P., Fraser, S., Finch, T., May, C.: Which quality of life score is best for glaucoma patients and why? BMC Ophthalmology 8, 2–8 (2008)
Gupta, N., Ycel, Y.H.: Glaucoma as a neurodegenerative disease. Curr. Opin. Ophthalmol. 18(2), 110–114 (2007)
Friedman, N., Geiger, D., Goldszmidt, M.: Bayesian Network Classifiers. Machine Learning 29, 131–163 (1997)
Breiman, L.: Random Forests. Machine Learning 45(1), 5–32 (2001)
Foster, P.J., Buhrmann, R., Quigley, H.A., et al.: The definition and classification of glaucoma in prevalence surveys. Br. J. Ophthalmol. 86(2), 238–242 (2002)
Gordon, M.O., Beiser, J.A., et al.: The ocular hypertension treatment study: baseline factors that predict the onset of primary open- angle glaucoma”. ArchOphthalmol. 120(6), 714–720 (2002)
Miglior, S., Pfeiffer, N., et al.: Predictive factors for open angle glaucoma among patients with ocular hypertension in the European glaucoma prevention study. Ophthalmology 114(1), 3–9 (2007)
Gordon, M.O., Torri, V., et al.: Validated prediction model for the development of primary open-angle glaucoma in individuals with ocular hypertension. Ophthalmology 114(1), 10–19 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Elfattah, M.A. et al. (2014). An Improved Prediction Approach for Progression of Ocular Hypertension to Primary Open Angle Glaucoma. In: Kömer, P., Abraham, A., Snášel, V. (eds) Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014. Advances in Intelligent Systems and Computing, vol 303. Springer, Cham. https://doi.org/10.1007/978-3-319-08156-4_40
Download citation
DOI: https://doi.org/10.1007/978-3-319-08156-4_40
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08155-7
Online ISBN: 978-3-319-08156-4
eBook Packages: EngineeringEngineering (R0)