Artificial intelligence in medicine. History and prospects

Abstract

Today, artificial intelligence (AI) is viewed as a key driver of digital transformation in healthcare. However, the journey toward modern diagnostic systems and personalized medicine has spanned more than half a century and involved several stages, from theoretical concepts to full-scale clinical integration. Currently, AI is permeating all areas of medicine: from diagnostic imaging to surgery, from epidemiology to nutrition, and from genomics to the assessment of chronic disease risks [29]. Traumatology and orthopedics occupy a special place in this context, as AI technologies open up new possibilities for understanding tissue morphogenesis, planning surgical interventions, predicting outcomes, and preventing complications. In this article, we trace the evolution of medical AI, from the inception of the «thinking machine» concept to modern deep learning algorithms, and examine practical examples of AI applications in orthopedics and related fields, from the morphogenesis of knee ligaments [27] and the choice of osteosynthesis method for tibial fractures [18] to the development of validated osteoarthritis risk scales [28], the stratification of decompensated osteoarthritis based on phenotyping and endotyping [20], and the prevention of osteoporotic fractures using internal load-shunting techniques [19, 11].