Two-decade dialogue between artificial intelligence and osteoporosis: research trajectories and frontier projections under bibliometric and visual analysis

Abstract

This study represents the first comprehensive bibliometric analysis of research on artificial intelligence in the field of osteoporosis. It not only outlines the field's development trajectory and emerging frontiers but also highlights the research focus on AI technologies, particularly deep learning. Furthermore, it emphasizes critical challenges in clinical translation, such as algorithm optimization, model interpretability, and ethical privacy concerns. By systematically identifying key contributors, collaborative networks, and evolving research fronts, this study provides a foundational roadmap for the field. It offers strategic priorities for researchers to address methodological gaps, serves as a reference for clinicians to understand the evolving technological toolkit, and provides a basis for policymakers to promote interdisciplinary collaboration.

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