Introduction. Technological progress and recent advances in artificial intelligence (AI) have led to the emergence of solutions aligned with key trends in global education – enhanced flexibility, adaptivity, and personalization of the learning process.
One of the major challenges of medical education is the exponential growth of scientific information and the accumulation of extensive databases of current and past research. A potential solution lies in the development of an intelligent system based on AI and data storage technologies capable of automating information retrieval, analysis, and processing.
The aim of this study was to design and develop the core modules of an intelligent cross-platform system «DocAI» using natural language processing (NLP) and graph database technologies to optimize the educational process in medical universities.
Materials and Methods. A comprehensive analysis of global and medical education trends was carried out. The study included a literature review and methodological assessment of digital transformation and personalization in educational environments, a Customer Development (CustDev) study, and a competitive analysis of AI-driven educational solutions.
Results. A prototype of the intelligent cross-platform system was developed to address the main challenges of educational process optimization – automation of information retrieval, analysis, and processing with adaptation to the individual needs and knowledge level of students, as well as efficient management of large data volumes. The prototype includes a modular architecture: the NLP module generates responses for users; the graph database module ensures flexible and scalable knowledge storage; the information extraction module retrieves relevant data from various sources.
Conclusion. The development of the intelligent cross-platform system «DocAI», based on natural language processing and graph database technologies, represents a relevant and promising approach to optimizing the educational process and facilitating the gradual integration of AI-enabled education (AIEd) into academic environments.
