Abstract
Vascular map within the inner surface of retina provides insights about ophthalmic abnormalities or early signs of different eye diseases. Devising a straight forward strategy to analyze the vascular map is quite challenging, given the complex and delicate nature of these vessels, as well as the high level of noise in the data. This article outlines a new method for analyzing vascular map by extracting various features and allocating weightage to these features. The most influential features in identifying the vascular map have been determined using a method called Permutation Importance. Final model is built using these highly qualified features. The performance of the model has been validated using internationally recognized standards and found to be among the top performers in its category.
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