[dipl] Perustieteiden korkeakoulu / SCI

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Browsing [dipl] Perustieteiden korkeakoulu / SCI by Author "Aaltonen, Juho"

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  • Application of linear machine learning methods for the diagnosis of mild traumatic brain injuries
    (2022-05-16) Aaltonen, Juho
     Perustieteiden korkeakoulu | Master's thesis
    Diagnosis of mild traumatic brain injury (mTBI) is challenging regardless of the high number of cases worldwide. Structural imaging findings are often lacking, and the aberrations in behavior are not specific to mTBI. Most mTBI patients recover rapidly without any prolonged symptoms, but 10-15% suffer from prolonged symptoms. Neurophysiological studies have demonstrated abnormal slow-wave (< 7 Hz) activity in mTBI compared with healthy controls when measured early after the trauma, but the analysis requires specific expertise. In this master's thesis, linear machine learning methods' ability to separate mTBI patients from healthy controls based on their magnetoencephalographic (MEG) brain activity is studied. Three widely used machine learning methods were used: linear discriminant analysis (LDA), support vector machine (SVM), and logistic regression (LR). The machine learning methods were applied on resting-state MEG power spectra (1-88 Hz) from two independent datasets. The results showed that it is possible to separate mTBI patients and healthy controls from each other based on their power spectra with median accuracy of 80-90%. There was no significant difference between the used machine learning methods, and the results were consistent between the two datasets. This suggests good performance of easily applicable linear machine learning methods also for clinical use for finding the patients who may benefit from close follow-up during the recovery period.