Аңдатпа
This paper provides a comprehensive analysis of the evolution of dermoscopy and the integration of artificial intelligence within clinical practice, specifically addressing early skin cancer detection in the Republic of Kazakhstan. Given that skin lesions remained among the top three oncological pathologies in the country between 2012 and 2022, objective screening is now a national priority. The study involved a multi-stage search across international repositories, resulting in a selection of twenty-six representative sources, including randomized controlled trials and meta-analyses. The findings trace the methodological transformation from the qualitative scales of the 1990s to the current era of digital dominance. Contemporary data confirm the technological superiority of convolutional neural networks, which demonstrate area under the curve values ranging from 0.86 to 0.99, often exceeding expert performance. While early observations focused on morphological structures, the current focus has shifted toward deep learning and total digital monitoring, despite persistent risks associated with real-world artifacts and out-of-distribution data. The analysis confirms a paradigm shift toward hybrid intelligent systems. In Kazakhstan, this process is supported by national strategic concepts and the Law on Artificial Intelligence, integrated into the 2026 health legislation. However, implementation at the primary healthcare level requires overcoming the lack of local datasets that account for regional skin phototypes. This study establishes a roadmap for technology integration, emphasizing that clinical validation and international cooperation are vital factors for improving patient survival rates during medical digital transformation.