Data visualization and clustering in the task of system analysis of the patients examination results in the initial stages of cognitive impairment

There are several numbers of diseases and conditions which contribute the progress of cognitive impairment and deterioration of cognitive functions compared to an individual norm. Currently, the causes and progression of cognitive impairment are poorly researched. This paper presents a system analysis of data including 152 patients and the results of their examination. Various machine learning models were used in the research, including classification and clustering algorithms. Methods of data preprocessing and dimension reduction were used for visualization. The result models have demonstrated the possibility of applying the latest artificial intelligence approaches for data analysis in the medical field. It was possible to achieve an accuracy of the cognitive impairment diagnosis in the initial stages of 75% despite the small data set.