A machine learning approach on classifying orthopedic patients based on their biomechanical features

Abstract

A person’s orthopedic health condition can be detected from his biomechanical features. Application of machine learning algorithms in medical science is not new. Different algorithms are applied to detect diseases and classify patients accordingly. This paper aims to assist specialists to predict the type of orthopedic disease. In this paper we have applied various machine learning algorithms to find out which one works most accurately to detect and classify orthopedic patients. Each of the patients in the dataset is represented by six biomechanical attributes derived from the shape and orientation of pelvis and lumbar spine. We performed our operation in two stages and got an average accuracy of more than 90 percent for most of the algorithms, whereas Decision Tree (DT) algorithm stood out from the rest providing 99% accuracy.