Machine Learning Approaches to Predict Scoliosis

Scoliosis seriously affects the physical and mental health of patients. Therefore, machine learning approaches were used to predict whether the subject was scoliosis patient or not by physical characteristics and electromyography (EMG) ratios. One hundred and six subjects, including 33 healthy subjects and 73 subjects with scoliosis, have been involved in this study. However, only about half of the predictions were correct. This may because of the small dataset, and the relatively weak relationship between the features (age, height, weight, gender, and EMG ratios) and the occurrence of scoliosis. This present work served as an initial step for the application of artificial intelligence in scoliosis prediction. However, it is significant and necessary for a greater effort in this topic.