AI in pharmacy education: a comparative visualization analysis of global and Chinese research trends
Abstract
Background: The rapid integration of Artificial Intelligence (AI) into healthcare necessitates a paradigm shift in pharmacy education to prepare future-ready professionals. However, the global trajectory of this educational evolution and the distinct strategic approaches between different regions remain under-explored. This study aims to systematically map the global and Chinese research landscapes, identifying evolutionary trends, pedagogical shifts, and core competency requirements in the intelligence era.
Methods: A comparative visualization analysis was conducted using CiteSpace (6.4.R1) on literature retrieved from the Web of Science (WoS) Core Collection and China National Knowledge Infrastructure (CNKI) covering publications up to December 31, 2025 (data retrieval was conducted in early 2026). We employed co-occurrence clustering and burst detection to analyze publication trends, institutional collaborations, and keyword evolution. The study specifically examined the divergence and convergence of educational strategies between global and Chinese contexts.
Results: A total of 240 English and 118 Chinese high-relevance articles were analyzed, revealing a rapid growth trajectory characterized by a logarithmic pattern, with universities as primary research hubs. The analysis identified three critical pedagogical transitions: Assessment Transformation: A shift from rote memorization to complex clinical reasoning, driven by Gen AI tools; Pedagogical Innovation: The…
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