Use HMM and KNN for classifying corneal data

TL;DR

This paper proposes a hybrid classification approach combining HMM and KNN to improve the accuracy of classifying corneal topography data for medical applications.

Contribution

It introduces a novel method integrating HMM and KNN to optimize corneal data classification, specifically for LASIK topography analysis.

Findings

HMM and KNN effectively classify corneal data

The combined classifier improves accuracy over individual methods

Markov models enhance topography classification

Abstract

These days to gain classification system with high accuracy that can classify complicated pattern are so useful in medicine and industry. In this article a process for getting the best classifier for Lasik data is suggested. However at first it's been tried to find the best line and curve by this classifier in order to gain classifier fitting, and in the end by using the Markov method a classifier for topographies is gained.