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Detection of keratoconus by semi-supervised learning

Keratoconus, is a non-inﬂammatory disorder of the eye in which structural changes within the cornea cause it to thin and change to a more conical shape which leads to substantial distortion of vision. Current methods for the detection of the disease mainly are Supervised learning approaches. Our goal is to label suspect patients who have not been clinically diagnosed(unlabeled data). Hence, we propose a new model, which integrates Manifold learning techniques with Semi-Supervised learning, to maximize the utility of the unlabeled data.