The possibilities of using digital big data sets in the field of telemedicine are presented. The main characteristics of big data are: large volume, high speed of updates, diversity, reliability, variability, value. The types of analytical tasks that can be solved using advanced methods of "big data" analysis are shown. The application of telemedicine technologies in the prevailing conditions of the epidemiological situation is stated. Description of the essence of digital transformation of the healthcare system. Functionality of electronic medical records of patients. Project of a unified state digital healthcare platform. Processing of personal personal data of patients of medical institutions. Machine learning goal sets in academic research, industry, and competitive data analysis. Promising directions of using artificial intelligence technology in the field of medicine. Using teleophthalmology as an example, the modern directions of the industry development are described. Machine learning for big data processing through the practice of an ophthalmologist. Deep Learning - solutions for the analysis of biomedical images. Deep Learning in Fundus Image Recognition. Convolutional neural networks in the diagnosis of diseases of the organs of vision. Preparing high-quality datasets for training algorithms. Advances in pathology recognition on retinal images. The purpose and place of telehothalmology in the work of an ophthalmologist. Interpretability principles for deep machine learning models. The concept of predictive, preventive, personalized and participatory medicine. Analyze mobile data at the application level. Existing mobile applications in teleophthalmology. Obstacles to the implementation of computer software in the medicine of eye diseases. Promising areas of research in ophthalmology for technicians.

Keywords: big data, teleophthalmology, artificial intelligence, machine learning, deep learning