Alma Šehanović’s scientific contributions

Human brain counts in a completely different way from conventional digital computers. Neurons are five to six rows of size slower than digital logic. There are human natural and artificial neural networks. The artificial nets are very similar to the human brain. The model of neurons, the mathematical model and the simulation models in the Matlab program will be presented. Matlab is a suite of high-level math labs that contain a set of tools that enable the user to easily and efficiently solve certain problems. Taking into account Matlba's capabilities, we think it is an ideal solution for the implementation of artificial neural networks and the ways of implementing algorithms for learning them. By simulation, we came to the conclusion that the two-layer network is a better choice than the one with one. In the paper, two types of neural networks will be presented using ADALINE and NANR (linear and nonlinear nonlinear networks). Different number of iterations in nonlinear networks will lead to improvement of network topology up to improving output from the neural network. This paper investigates the integration of fuzzy logic and neural networks for disease detection using the Matlab environment. Disease detection is key in medical diagnostics, and the combination of fuzzy logic and neural networks offers an advanced methodology for the analysis and interpretation of medical data. Fuzzy logic is used for modeling and resolving uncertainty in diagnostic processes, while neural networks are applied for in-depth processing and analysis of images relevant to disease diagnosis.

This paper investigates the integration of fuzzy logic and neural networks for disease detection using the Matlab environment. Disease detection is key in medical diagnostics, and the combination of fuzzy logic and neural networks offers an advanced methodology for the analysis and interpretation of medical data. Fuzzy logic is used for modeling and resolving uncertainty in diagnostic processes, while neural networks are applied for in-depth processing and analysis of images relevant to disease diagnosis. This paper demonstrates the development and implementation of a simulation system in Matlab, using real medical data and images of organs for the purpose of detecting specific diseases, with a special focus on the application in the diagnosis of kidney diseases. Combining fuzzy logic and neural networks, simulation offers precision and robustness in the diagnosis process, opening the door to advanced medical information systems.

The paper presents the results of the research in the teaching of mathematics, ie, units that deal with the problems of solving problems in teaching mathematics. The aim of the research is to present the extent to which problem teaching in mathematics teaching is represented in the school, in which the advantage of problem teaching, who are participants in such teaching process, is regular or additional teaching. There is certainly the question of whether a new way of doing mathematics through problem solving can be introduced through the problems of teaching mathematics. The methods of theoretical analysis and surwey research method were used and from the instruments a questionnaire was constructed for research purposes. The sample of this paper consisted of 400 students in the area of Lukavac Grad municipality, Lukavac Mesto, and eighth and ninth grade students. The research results of this paper show that slightly better students in mathematics prefer these mathematical topics.