This paper aimed to increase accuracy of an Alzheimer’s disease diagnosing function that was obtained in a previous study devoted to application of decision roots to the diagnosis of Alzheimer’s disease. The obtained decision root is a discrete switching function of several variables applicated to aggregation of a few indicators to one integrated assessment presents as a superposition of few functions of two variables. Magnetic susceptibility values of the basal veins and veins of the thalamus were used as indicators. Two categories of patients were used as function values. To increase accuracy, the idea of using artificial neural networks was suggested, but a feature of medical data is its limitation. Therefore, neural networks based on limited training datasets may be inefficient. The solution to this problem is proposed to preprocess initial datasets to determine the parameters of the neural networks based on decisions’ roots, because it is known that any can be represented in the incompletely connected neural network form with a cascade structure. There are no publicly available specialized software products allowing the user to set the complex structure of a neural network, which is why the number of synaptic coefficients of an incompletely connected neural network has been determined. This made it possible to predefine fully connected neural networks, comparable in terms of the number of unknown parameters. Acceptable accuracy was obtained in cases of one-layer and two-layer fully connected neural networks trained on limited training sets on an example of diagnosing Alzheimer’s disease. Thus, the scientific hypothesis on preprocessing initial datasets and neural network architecture selection using special methods and algorithms was confirmed.
The study of human gait is of interest in determining its individual characteristics that affect the loads experienced by the joints of the lower extremities. To analyze the gait in the lateral projection, an experiment was carried out with placed markers on the subject's body to determine the interarticular angles in the hip, knee and ankle joints. The graphs of the dependences of these angles on time were built, corresponding to a certain phase of the step. It was found that the range of changes in the angle in the left ankle joint in the subject was significantly different from the dependence obtained for the right joint. Based on the subject's anamnesis, we associate these differences with the fact that there was an ankle joint injury that affected the condition of the ligamentous apparatus of the joint. In further work, it is proposed to consider a person's gait not only in the lateral, but also in the frontal (anteroposterior) plane to assess all movements in the joints, especially those associated with the abduction of the limbs and the human body from the vertical line on the specified plane.
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