The conducted studies related to the substantiation of the knowledge base, which ensures the prediction of the duration of inpatient treatment of diabetes in children based on the use of the developed neural network model of direct communication. The paper proposes an approach and prepares data for predicting the duration of inpatient treatment of diabetes in children. The substantiation of the parameters of the feedforward neural network model for predicting the course of inpatient treatment of diabetes was performed, and the accuracy indicators of the proposed model were also evaluated. The proposed approach to predicting the duration of inpatient treatment of diabetes in children is based on the use of forward propagation neural networks and involves implementing nine stages. The peculiarity of this approach is that the formation of databases and knowledge is carried out based on taking into account the peculiarities of inpatient treatment projects. It is based on a computer analysis of historical data and involves modeling, which provides a systematic consideration of the relationships between factors and the duration of inpatient treatment of diabetes in children.
Based on the use of the developed approach, as well as using the prepared data, the parameters of the neural network model of direct communication for predicting the duration of inpatient treatment of diabetes in children are substantiated. The accuracy indicators of the model were evaluated. The proposed rational feedforward neural network model involves two layers (the first is the Dense type with 64 neurons and the ReLU activation function, and
the second is the Dense type and 1 neuron). The total number of model parameters is 385. In the proposed model, the learning rate is 0.0001.