The article discusses the methods and approaches developed by the authors for the recommendation system, which are aimed at improving the quality of rehabilitation of the patient during respiratory training. To describe the training, we developed our own language for a specific subject area, as well as its grammar and syntax analyzer. Thanks to this language, it is possible to build a devereve describing a specific patient's training. Two main methods considered in the article are applied to the resulting tree: "A method for analyzing problem areas during training by patients" and "A method for fuzzy search of similar areas in training". With the help of these methods, it is proposed to analyze the problem areas of patients' training during rehabilitation and look for similar difficult areas of the patient to select similar exercises in order to maintain the level of diversity of tasks and involve the patient in the process.

Keywords: Recommendation system, learning management system, rehabilitation, medicine, respiratory training, marker system, domain-specific language, Levenshtein distance

The results of clinical trials are the main source of information in the implementation of medical activities in accordance with the principles of evidence-based medicine. At the moment, there are no information systems that would allow a doctor to select clinical studies within the framework of nosology that best match the profile of a particular patient, in order to further analyze their results and select therapy. The aim of the study was to improve the existing process of searching for clinical trials by using the prioritization method according to the inclusion criteria set by the doctor during the selection. To achieve this goal, the following tasks were implemented, namely, the process of selecting and searching for clinical trials by doctors was studied and the method of searching for clinical trials by doctors and the allocation of the necessary criteria was worked out. The team of authors proposed an algorithm for searching for clinical trials according to inclusion criteria, which in turn will significantly increase the effectiveness and reduce the time for searching and choosing therapy.

Keywords: clinical studies, criteria search algorithms, criteria search methods, including factors, search for the nearest class, services