DEVELOPMENT OF PRINCIPLES OF ASSEMBLY-BASED INFORMATION LEARNING IN THE TASKS OF MEDICAL DIAGNOSTICS, IN PARTICULAR, THE DETECTION OF PRECANCEROUS CONDITIONS

Rubekina Julia Sergeevna

Oral cancer is one of the most aggressive and dangerous types of cancer, claiming the lives of thousands of people every year. In recent decades, there has been an alarming trend in the spread of the disease: the number of cases of oral cancer is increasing, while young people are also suffering from the disease. Despite the fact that oral cancer is a visually detectable neoplasm, the rate of advanced cases of the disease continues to be critically high. Of particular importance is the development of flexible screening algorithms that take into account specific risk factors. This approach will make it possible to move from simple compliance with formal standards to the creation of a truly effective and working system for the early detection of oral diseases [6]. However, effective diagnosis of cancer and precancerous diseases of the oral cavity requires in-depth knowledge of their clinical manifestation and modern methods of their detection. The subject of the development is an automated diagnostic technique based on hardware – multispectral imaging in the UV and IR ranges combined with a standardized positioning system, and software – an algorithm for data preprocessing and ensemble classification of components.

Keywords:data processing, automated diagnostics, ensemble classification, screening, early diagnosis, automated system.