Artificial intelligence in healthcare: historical trajectory, challenges and prospects (1960-2025)

Abstract

In the 21 st century, artificial intelligence (AI) has become one of the key drivers of the digital transformation of healthcare. Its implementation spans virtually all levels, from primary care to high-tech clinics, enabling the automation of routine processes, increased diagnostic accuracy, and personalized treatment. Global challenges, such as population aging, the increasing prevalence and severity of chronic diseases, a shortage of healthcare professionals, and the need to ensure equal access to healthcare requires large-scale digital solutions. AI is viewed not only as a tool for optimizing clinical and administrative processes but also as the technological foundation for a new healthcare paradigm, shifting the emphasis from treatment to prevention and early detection. The choice of 1960-2025 time period for this study is due to the historical significance of these six decades in the development of AI in medicine. It was in the 1960s that the first health information systems appeared, marking the beginning of automated medical data processing. In subsequent decades, the development of expert systems, machine learning, deep learning, and generative models led to the formation of a multi-layered AI infrastructure in healthcare, and by 2025, these technologies had reached a high degree of integration into clinical practice.

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