Analysis of the use of artificial intelligence systems for the development of physical exercise programs during rehabilitation of nephrology patients

Abstract

Background. Artificial intelligence (AI) is a direction of mathematical computer modeling based on the abstract essence of mathematical thinking. Chronic kidney disease (CKD) is a nosological unit, its final stage (end-stage renal disease) has seen an exponential increase over the past decade and is considered by the World Health Organization as a global problem by cause of death. The global healthcare industry is one of the main planes for practical application of modern developments in the field of AI thanks to machine learning algorithms that provide new opportunities for solving the most complex problems of medicine and pharmacy. The purpose was to analyze the possibility of using physical exercise complexes (PECs) created by AI system in patients with CKD undergoing renal replacement therapy and to compare PECs created by AI with the list of PECs used in clinical practice (systematic reviews and meta-analyses) for rehabilitation care in nephrology. Materials and methods. Scientometric analysis of professional literature from electronic databases PubMed, Embase, Scopus and Web of Science, Cochrane CENTRAL was conducted. According to the purpose of the study, the following methods were used: bibliosemantic, systematic approach, descriptive modeling using AI systems — Gemini and ChatGPT. Results. AI systems (Gemini and ChatGPT) proposed exercise programs for patients with CKD that take into account different stages of rehabilitation (respiratory, aerobic, strength, stretching and relaxation). At the time of the descriptive modeling, the database used by Gemini and ChatGPT is sufficient for their routine use in the development of exercise therapy complexes for the rehabilitation of nephrological patients with different nosologies. Conclusions. Artificial intelligence is a tool in the hands of a physician to provide medical care; the quality of this tool will depend on the qualifications of the physician who will teach (machine learning) AI to use their knowledge and competencies to optimize the process of creating rehabilitation complexes for patients with kidney disease from the standpoint of evidence-based medicine.