The transformative impact of large language models in healthcare

Over the past decade, we have witnessed rapid technological advances in healthcare. The main signs of this are the provision of higher quality medical services, lower costs, and improved access to preventive measures. Modern digitalization is represented by various tools in the healthcare system. Support and further development in these areas is the key to, firstly, creating appropriate living conditions, secondly, increasing the age limit for the population, and thirdly, developing a healthy nation around the world. The object of this work is Large Language Models (LLMs), namely, the streamlining of actions for their application in the healthcare system, which is a driving factor for modern changes and improvement of this area of life support in general. This study presents the material on the application of artificial intelligence in the healthcare system through a comprehensive review of medical scientific literature, summarizing the practical application of large language models, and analyzing the main advantages and disadvantages of the current state of digitalization in the industry. By using the methods of observation, generalization, systematization and comparison, the authors have achieved results in determining the significance of the use of large language models. It is also determined that the introduction of artificial intelligence has positive results, but needs to be improved. The formalized and specific comparisons of the diagnoses made by a doctor and artificial intelligence do not coincide with the chosen treatment history, which indicates an imbalance and can potentially harm the patient. The results show the need to improve large language models. In general, this applies to issues such as training of medical staff, identification of implementation methods, systematization of management tools, and expansion of information system databases (including protection of patients' personal data).