A Study of Data Mining Techniques in Glaucoma Detection
Author(s):
R.Gomathi, R.Ramprashath, A.Gokulraja, M.Bharath, K.Sri Hari Vishnu
Keywords:
Glaucomatous, Aqueous humor, blood vessels, Data mining, Dataset, Data transformation,
Knowledge Discovery Technique.
Abstract
Glaucoma is that the second leading eye disease for blindness after cataracts and its detection is important to stop visual damage. Glaucoma is that the third leading explanation for blindness in India. Some frameworks are accustomed to detect the glaucoma in early stage using data mining and other techniques. Automation method to stipulate and locate blood vessels in image of the ocular fundus could be a tool useful to eye care specialist for purpose of treatment evaluation [1]. Using these styles of techniques the system will identify the glaucomatous eye which is ready to predict the progression of glaucoma. Because of this type of techniques the assisting ophthalmologist can detect and diagnose the glaucoma in earlier stage in order that our society will fight against the killer vision. This process of diagnosis and detection will be achieved through various data processing technique and algorithm like classification, clustering, association and fuzzy decision tree etc., during this study attributes like age, vital sign, diabetes, case history of assorted patients. With the assistance of this dataset can predict the accuracy result for glaucoma. In this approach of data mining patients can easily identify whether there are chances of getting glaucoma or not.
