Visualization of a graph model of medical drugs and their classes with subject to incompatibility

Abstract

Currently, the world is actively undergoing digital transformation, which is associated with the introduction of digital technologies in various fields. Methods for predicting and combating various types of diseases are being developed more and more actively. A separate place in this issue is given to pharmacology and reducing the risks of poly-pharmacotherapy. Works in this area have become more and more active in the last three years, and relate primarily to the problems of experimental medicine - the search for new drugs or classification of patients by images. In this connection, the development of algorithms for processing big data in the field of clinical pharmacology, including regulatory documents, instructions for the use of drugs, reliable medical resources for machine learning and building a knowledge base focused on practical application in real medical practice, is becoming increasingly important. One of the considered approaches for solving the problems described above is the search for an effective vector representation of the found concepts (word embedding) to build models of recommendations for the practical use of drugs based on the diagnosis and models for identifying their compatibility. The article presents a software tool for visualizing a graph model of medicines and their classes, considering their incompatibility. The problem of incompatibility of medicines is being investigated. The considered database of medicines, obtained from various sources, and the advantages of its use are described. The article presents the results of the developed prototype of a software tool that allows you to visualize a complete graph of relationships between drugs, a graph of incompatible drugs for a selected drug, and a graph of compatibility of two drugs. Graph model visualization provides a visual representation of complex relationships and allows researchers and pharmacologists to better understand interactions between drugs. The software offer the necessary tools to make informed decisions when prescribing medications and improve safety when using medicines.