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    An investigation of machine learning algorithms for prediction of lumbar disc herniation
    (Springer Heidelberg, 2023) Kocaman, Hikmet; Yildirim, Hasan; Goeksen, Aysenur; Arman, Gokce Merve
    The prevalence of lumbar disc herniation (LDH), which makes patients' daily activities more difficult and reduces their quality of life, has tended to increase recently. Many risk factors associated with LDH have been reported. In this study, LDH was predicted using machine learning techniques using measures of the lumbar paraspinal muscles, lumbar vessels cross-sectional area (CSA), and lumbar sagittal curve. Three hundred and forty-four individuals' MR scans were prospectively enrolled (264 with LDH and 80 healthy). Predictive factors were the lumbar sagittal curve and the cross-sectional areas of the lumbar paraspinal muscles and vessels from sagittal and axial MR images. The measurements have been analyzed via ten different and most common machine learning algorithms by considering a comprehensive parameter tuning and cross-validation process. The variable importance results have been also presented. XGBoost algorithm among all algorithms has provided the best results in terms of different classification metrics including f-score ( 0.830 ), AUC ( 0.939 ), accuracy ( 0.922 ), and kappa ( 0.779 ). The findings of this study demonstrated that cross-sectional areas of the quadratus lumborum and abdominal aorta can be utilized as a reliable indicator of LDH. Consequently, the developed model and the variables found to be important may guide to healthcare professionals to make more accurate and effective decisions in terms of prediction the LDH.
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    Comprehensive analysis of muscles wasting in disc herniation
    (Elsevier Sci Ltd, 2022) Goksen, Aysenur; Kocaman, Hikmet; Arman, Gokce Merve; Selcuk, Muhammet Lutfi
    Neuromuscular reeducation of the muscles that stabilize the spine is the basis of conservative treatment of disc herniation. Therefore, it is important to investigate how these muscles are affected by disc herniation. The aim of this study was to investigate the effect of disc herniation, herniation severity, patient age, and biomechanics on the lumbar stabilizer muscles. A total of 330 individuals, including 261 patients with disc herniations and 69 without disc herniation participated in this study. The cross-sectional areas (CSAs) of the lumbar stabilizer muscles and the lumbar lordosis angle were evaluated by magnetic resonance imaging (MRI), according to the severity of the disc herniation and the patient's age. In the patients with disc herniation, the CSAs of the quadratus lumborum (QL) and the multifidus (MF) muscles were decreased. The psoas major (PM) muscle CSA was higher in the patients with sequestered discs than in those with protruded and extruded discs. A negative relationship between the sagittal curve and the PM muscle CSA was found. In addition, MF muscle CSA was found to decrease at age 45 years and over. Although disc herniation negatively affects muscle CSAs, no linear relationship was found between the severity of the herniation and the muscle CSA. In addition, the PM muscle was found to be a strong compensatory muscle in disc herniation.