Modern technologies for medical data analysis in multiple sclerosis diagnosis

The diagnosis of multiple sclerosis (MS) requires the analysis of large volumes of complex medical data. Modern technologies, including machine learning, image processing, and time series analysis, provide new opportunities for automating diagnosis and prognosis. This paper examines key algorithms, such as convolutional neural networks (CNN) and time-series analysis methods, as well as software solutions, including 3D Slicer, TensorFlow, and SberMedAI. Their advantages, limitations, and prospects for clinical application are discussed.