Artificial intelligence in telemedicine: Topic modelling and network analysis of patents (1992–2024)

Background: Artificial intelligence (AI) is transforming telemedicine within the broader digital-health ecosystem, yet systematic evidence on its technological hotspots and long-run trajectories remains limited. Objective: To map the technological evolution of AI in telemedicine and identify innovation clusters and pathways that can inform policy, standards, and implementation planning. Methods: We analysed 1451 AI-telemedicine patents (1992-2024) from the PatSnap database using a text-mining pipeline that combines classification-based social network analysis (SNA) with latent Dirichlet allocation (LDA) topic modelling. Topics were organised by life-cycle phases to trace semantic evolution. Model robustness was assessed using topic coherence and perplexity scores. Network centrality metrics (degree, betweenness, closeness) were used to identify structurally influential technologies. Results: Four dominant trends emerged: (1) surgical robotics evolving from hardware optimisation to intelligent control (e.g. 'surgical' 0.045; 'robot' 0.042; 'control' 0.016); (2) multimodal data fusion supplanting transmission-only designs ('patient' 0.188; 'site' 0.117; 'data' 0.056); (3) convergence of AI and advanced connectivity (e.g. 5G) enabling personalised, patient-centred telemedicine; and (4) deep-learning image analysis extending from diagnostic support to early disease prediction ('image' 0.034; 'diagnosis' 0.022; 'early' 0.010). Centrality results position surgical robotics and data-fusion infrastructures as persistent long-run technological hubs. Conclusions: By integrating semantic topic evolution with structural network dynamics, this study provides an empirical overview of the technological evolution of AI-telemedicine. The findings highlight several priority domains, including data-fusion infrastructure, explainable imaging AI, and surgical and remote-care applications, offering insights relevant to digital-health policy and governance.