Prospects for the use of generative language models in the development of medical assistants

Generative language models, such as GPT, BioGPT, and Med-PaLM 2, open new horizons in the development of medical assistants capable of supporting physicians in diagnostics, treatment, and administrative tasks. This paper examines key application areas of these models, including medical data processing automation, clinical decision support, medical image analysis, patient monitoring, and interaction via telemedicine platforms. The advantages of generative models, such as improved diagnostic accuracy, workflow optimization, and personalized treatment, are analyzed. Additionally, challenges related to the reliability of generated data, ethical concerns, data privacy, and the "black box" nature of these models are discussed [1, 2, 3]. The study highlights that generative language models hold significant potential for transforming healthcare. However, their successful implementation requires the development of specialized solutions, adherence to ethical norms, and training of medical professionals in AI tools. The paper suggests directions for future research, including AI integration with telemedicine platforms and the establishment of new standards in medical artificial intelligence [4, 5]. It is emphasized that generative language models should be considered as auxiliary tools that enhance the capabilities of healthcare professionals rather than replace them. The adoption of such technologies must be based on a responsible approach, integrating scientific, technical, and medical aspects [6].