计算机科学
人工智能
背痛
分类器(UML)
逻辑回归
机器学习
腰痛
统计分类
模式识别(心理学)
医学
替代医学
病理
作者
Mutia A. Paramesti,Aisyah Fitriannisa Prawiningrum,Akhmad Dyma H. Syababa,Hugi Reyhandani Munggaran,Suksmandhira Harimurti,Widyawardana Adiprawita,Isa Anshori,Indria Herman
标识
DOI:10.1109/apcorise46197.2019.9318818
摘要
Most of old people usually suffer from a lower back pain. The main problem of this pain is the long recovery time. Some patients may be fully recovered from lower back pain for even years. Therefore, a preventive action is needed to be developed to prevent the lower back pain gets worsening. This paper presents a comparative study of lower back pain classification method using machine learning technique. The classification is performed using several algorithms. Moreover, a performance tuning using Grid Search method is also conducted. The results show that K-Nearest Neighbor algorithms provide the best classification accuracy as high as 87.2%. However, after tuning, the best classification accuracy as high as 86.7% obtained by using logistic regression classifier.
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