SIMULATION AND MODELING OF MEDICAL SCENARIOS WITH THE APPLICATION OF ARTIFICIAL INTELLIGENCE

Abstract

The processes of simulation and modeling in medicine are not new; they have been in use for a long time. The popularization of modern technologies, primarily Artificial Intelligence (AI), has significantly influenced this segment of medical practice. This particularly refers to the development of predictive models and the creation of intelligent simulators based on these technologies. These systems are built on AI concepts such as Machine Learning (ML) and Deep Learning (DL). They enable diagnosis, outcome prediction, data analysis, and patient privacy protection. Simulations and models based on AI have significant applications in medical education for both current and future medical professionals. The importance and utility of these systems have particularly come to the forefront during the COVID-19 pandemic, facilitating skill development in a controlled environment. However, the application of AI in medical simulation and modeling presents challenges and limitations, including technical, ethical, and legal aspects. Technical issues involve selecting appropriate neural network topologies and the lack of data for system training, while ethical and legal concerns include the lack of regulation and accountability in case of errors. The future development of these technologies in this field involves integrating human and artificial capabilities to achieve better outcomes for patients. A multimodal approach to AI and the development of large-scale language models promise to enhance the performance of AI systems, which will positively impact the segments of medical practice where they are applied. The aim of this paper is to explore the current capabilities, challenges, and future directions of these technologies in medicine.