BOHR International Journal of Smart Computing and Information Technology

The macula is a small area of the retina which is especially very important for good eyesight. The age- related
macular degeneration (AMD) is a type of visual impairment that can cause blindness or even loss of eyesight.
AMD was a dangerous and progressing chronic disease that affects people over the age of 60 years. One of the
most common symptoms of this condition is the appearance of a type of extracellular material called the drusen.
Detecting this condition using an imaging technique known as optical coherence tomography (OCT) can help to
prevent further damage to the eyes. The motivation behind this work is to test machine learning (ML) with OCT
images for the identification of retinal disease. OCT retinal images consist of normal retina and AMD. ML algorithms
were used to classify 261 OCT images to determine if the person was normal or macular. The proposed method
for diagnosing between diseased and healthy conditions has a classification accuracy that considerably exceeds
beyond the current state of the art. This work will be used in developing further ML concepts in the diagnosis of
ocular disorders and diseases.