On Determination of Ophthalmic Examinations Using Support Vector Machines

In this paper, a method of determining examination groups is presented for new outpatients visiting the department of ophthalmology, using support vector machines (SVM´s). Assuming that interview sheets are divided into four classes, the proposed method copes with the examination determination as the classification of the sheets. The data are generated from handwriting sentences in the sheets, and they are arranged in the form of a matrix. Some nouns and adjectives in the sentences are chosen as elements of the matrix, and are assigned to columns of the matrix. The sentences in the sheets are assigned to rows of the matrix. Frequencies of the chosen words appearing in the sentences are basically given as element values in the matrix, and weighting is applied to element values associated with the words having comparatively high frequencies for sentences belonging to two classes at most. Normal SVM learning constructs a discrimination model, and defines four discriminant functions associated with the model. Since one-versus-all approach is employed, the class of data to be examined is determined according to output values of the four functions. It is established that the determination made by the proposed method achieves as favorable accuracy as the first determination made by an average ophthalmologist.