Dejan Georgiev

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The paper describes the process of knowledge elicitation for a neurological decision support system. To alleviate the difficult problem of knowledge elicitation from data and domain experts, we used a recently developed technique called ABML (Argument Based Machine Learning). The paper demonstrates ABML's advantage in combining machine learning and expert(More)
The aim of this study was to determine the effects of alpha neurofeedback and EMG biofeedback protocols for improvement of musical performance in violinists. The sample consisted of 12 music students (10 violinists and 2 viola players) from the Faculty of Music, Skopje (3 males, mean age of 20 +/- 0 and 9 females, mean age = 20.89 +/- 2.98). Six of them had(More)
OBJECTIVE The paper describes the use of expert's knowledge in practice and the efficiency of a recently developed technique called argument-based machine learning (ABML) in the knowledge elicitation process. We are developing a neurological decision support system to help the neurologists differentiate between three types of tremors: Parkinsonian,(More)
Argument Based Machine Learning (ABML) was recently demonstrated to offer significant benefits for knowledge elicitation. In knowledge acquisition , ABML is used by a domain expert in the so-called ABML knowledge refinement loop. This draws the expert's attention to the most critical parts of the current knowledge base, and helps the expert to argue about(More)
The article reflects the fact, that concepts like decision making and free will have entered the field of cognitive neuroscience towards the end of 20 th century. It gives an overview of brain structures involved in decision making and the concept of free will; and presenting the results of clinical observations and new methods (functional neuroimaging,(More)
When choosing between two options, sufficient accumulation of information is required to favor one of the options over the other, before a decision is finally reached. To establish the effect of dopaminergic medication on the rate of accumulation of information, decision thresholds and speed-accuracy trade-offs, we tested 14 patients with Parkinson's(More)
To date, many different approaches have been used to study the impairment of motor function in Parkinson's disease (PD). Event-related potentials (ERPs) are averaged amplitude fluctuations of the ongoing EEG activity that are time locked to specific sensory, motor or cognitive events, and as such can be used to study different brain processes with an(More)
Parkinson's disease (PD) patients show signs of cognitive impairment, such as executive dysfunction, working memory problems and attentional disturbances, even in the early stages of the disease. Though motor symptoms of the disease are often successfully addressed by dopaminergic medication, it still remains unclear, how dopaminergic therapy affects(More)