Family Medicine as an independent medical discipline is relatively young in the countries of Southeast Europe. Still are used the old models of all forms of education in this module, although most countries accepted Bologna undergraduate teaching concept and already implement it with greater or lesser success. Measuring the effects of the qualities of these concepts and models is not done systematically nor in uniform manner, so it could not be compared by the unique variables measuring the quality of education curricula, and especially the quality of education level of the graduates at the first, second and third degree courses and other forms of education. This paper provides a comparative overview of the state of education in the area of family medicine in the region. It creates comparison according to the study duration for undergraduate and postgraduate studies, doctoral studies and specialized studies in specified areas. What stand out are the proposals to improve education in the field of family medicine in the region.

This paper focuses on the improvements of digital filters with a highly sharp transition zone on the Xilinx FPGA chips by combining a sharpening method based on the amplitude change fun ...

This research introduces a new method for functional brain imaging via a process of model inversion. By estimating parameters of a computational model, we are able to track effective connectivity and mean membrane potential dynamics that cannot be directly measured using electrophysiological measurements alone. The ability to track the hidden aspects of neurophysiology will have a profound impact on the way we understand and treat epilepsy. For example, under the assumption the model captures the key features of the cortical circuits of interest, the framework will provide insights into seizure initiation and termination on a patient-specific basis. It will enable investigation into the effect a particular drug has on specific neural populations and connectivity structures using minimally invasive measurements. The method is based on approximating brain networks using an interconnected neural population model. The neural population model is based on a neural mass model that describes the functional activity of the brain, capturing the mesoscopic biophysics and anatomical structure. The model is made subject-specific by estimating the strength of intra-cortical connections within a region and inter-cortical connections between regions using a novel Kalman filtering method. We demonstrate through simulation how the framework can be used to track the mechanisms involved in seizure initiation and termination.