## 1 Introduction  
Age-related macular degeneration (AMD) is the leading cause of visual dysfunction and blindness in developed countries and a rising cause in underdeveloped countries. AMD is characterized by progressive degeneration of the macula, causing central field vision loss. The global prevalence of AMD is 8.7% worldwide [1; 2]. Importantly, at least 1 out of 10 Hispanics have AMD, which is slightly higher than the global rate [3]. Several studies are focused on the risk factors for European [4], Asian [2],and American [5] non-Hispanic population. Genetic variants, older age, and cigarette smoking are common examples of accepted risk factors [6].  
Age-related cataract is also a frequent eye disorder and the leading cause for reversible blindness. The World Health Organization [7] current estimates for its prevalence are around 65.2 million persons affected with moderate or severe distance vision impairment or blindness worldwide. As the life expectancy of the population rises, the number of people suffering from AMD is also increasing [8]. This fact is causing a very expensive health care burden for the states in addition to the deterioration of the quality of life of the people suffering from AMD.  
Historically, traditional statistical methods were used to determine high-risk factors of diseases, and predictive models were built to aid the physician in the diagnosis of AMD [9, 10]. For instance, [PERSON] et al. [6] presented a systematic review and a meta-analysis for the selection of risk factors in several populations. In that review, the authors reported previous cataract surgery as a strong risk factor for neovascular AMD. The authors analyzed data from different ethnic groups and they found cataract surgery to be one of the strong and consistent risk factors for late AMD. On the other hand, [PERSON] et al. [11] conducted some research to detect the associations between cataract and cataract surgery with early and late age-related macular degeneration over the American population. The conclusions of the study were that neither cataract nor cataract surgery were associated with a greater chance of developing early AMD.  
Results from several epidemiological studies regarding the association between bilateral cataracts and AMD have been inconsistent [12, 13, 14]. For this reason, more research will help to conclude whether cataracts and cataract surgery are major risk factors for AMD disease.  
In the last decades, machine learning methods and dimensionality reduction techniques have been found to be useful for medical diagnosis and finding high-risk factors, specifically for AMD disease. For example, [PERSON] et al. [15] used multifactor dimensionality reduction (MDR) and grammatical evolution of neural networks (GENN), in addition to logistic regression, to predict the risk for individuals of suffering from AMD disease.  
In this paper, we present a machine learning approach to analyze the relevance of cataract as a risk factor for AMD, in order to shed light regarding the controversy between inconclusive points of view in this matter. We investigated the association between two polymorphisms in the Complement Factor H (_CFH_) gene over the Mexican population. These polymorphisms have been previously investigated in several populations in other studies such as that of [PERSON] et al. [16].  
The rest of the paper is organized as follows. In Section 2, we describe the materials used for data collection and procedure used to analyze if cataracts are a risk factors for AMD. In Section 3, we present the results of our machine learning approach. We discuss our results and findings in Section 4. Section 5 concludes the paper and highlights future work.