The role of artificial intelligence and digital pathology in telemedicine solutions for histopathological diagnosis: a bibliometric analysis

Abstract

Background. Oncological diseases remain one of the leading causes of mortality worldwide, emphasizing the importance of improving the accuracy and timeliness of pathomorphological diagnostics. At the same time, traditional pathohistological assessment is resource-intensive, dependent on subjective factors, and limited by a shortage of qualified specialists, especially in resource-limited countries. The integration of telemedicine, digital pathology, and artificial intelligence is considered a promising approach to optimizing diagnostics. Purpose – this study aims to perform a comprehensive bibliometric analysis and systematically review scientific data on the application of artificial intelligence and telemedicine for optimizing pathohistological diagnostics. Materials and Methods. The analysis was performed based on 5628 scientific publications indexed in the Scopus database for the period 2009–2025, using bibliometric analysis tools and VOSviewer software. The search was conducted using the following keywords: deep learning, artificial intelligence, digital pathology, telemedicine. Results. The study results indicate a rapid increase in the number of scientific publications starting from 2017, peaking in 2024, reflecting the dynamic development and clinical translation of digital pathology and artificial intelligence technologies. The geographic distribution of scientific activity demonstrates the dominance of the USA, China, and the United Kingdom. Thematic clustering using VOSviewer identified three main research directions: deep learning systems for medical image analysis, digital pathology, and the application of technologies in clinical practice. Chronological analysis indicates an evolution from basic diagnostic support systems to integrated solutions combining artificial intelligence, telemedicine, and personalized medicine. Conclusions. The data confirm the potential of artificial intelligence and telemedicine to improve the accuracy, reproducibility, and accessibility of diagnostics. At the same time, the analysis highlights unresolved ethical, legal, and standardization challenges, the resolution of which is a necessary condition for the broad and safe implementation of these technologies.

Ähnliche Arbeiten