Аннотация:
The direction of research is the development of principles and
methods for making scientifically based decisions in the design
and additive manufacturing of bone substitutes based on
apatite-biopolymer composites with functional properties
depending on the nature of the localization of the cavity bone
defect and its size. The relevance is due to the fact that the
development of an intelligent decision-making support system
based on neural network modeling, the development of
methods for their training, tabagato-criterion optimization of
design processes, will allow the creation of three-dimensional
solid models of defects taking into account their spatial structure
and bone substitutes for the synthesis of biomaterials with
controlled composition, porosity and mechanical strength,
which are optimal for a specific area of bone replacement, which
will increase the effectiveness of treatment and prosthetics in
orthopedics and traumatology. A set of methods for analyzing
images of bone tissue, taking into account its spatial structure,
which are obtained by sensors of different physical nature, with
the use of neural network models, development of methods of
their design, optimization, and training is proposed. A
modification of the method of learning neural networks based
on gradient descent, based on the application of the theory of
nonlinear dynamics, is proposed. Corresponding theoretical
provisions have been developed.
