International Journal of Artificial Intelligence and Neural Networks
Author(s) : A.K.A.WIJEWICKRAMA, K. A. DILINI T. KULAWANSA
In modern medical field detecting nipping is done manually by ophthalmologists to detect hypertension of a patient. This is mainly done by the doctor using a gonioscope or by examines a fundus image of the patient. This proceeding may takes extensive amount of time and when the ophthalmologist has large number of patients to examine, this can be frustrating. In this review I discuss how this process can be automated under the supervision of an expert so that when the ophthalmologist receives the fundus image of a patient, he will get data of that patient that if he has hypertension symptoms in his fundus or not. With an assisting tool like this the efficiency of a typical fundus examine process can be increased in an exponential rate. A system like this will also open more and more ways to other approaches regarding same methods and technologies.