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ORIGINAL RESEARCH article

Front. Cell Dev. Biol.

Sec. Stem Cell Research

This article is part of the Research TopicAI and Big Data Integration in Orthopedic Regenerative MedicineView all 4 articles

AI and Big Data driven knowledge mapping of exosome–hydrogel research in orthopedic regeneration and tissue engineering

Provisionally accepted
Qinghan  LiQinghan Li1Liming  LouLiming Lou2Shuaishuai  WangShuaishuai Wang1Minglei  ZhangMinglei Zhang1*
  • 1China-Japan Union Hospital, Jilin University, Changchun, China
  • 2Beijing Forestry University, Beijing, China

The final, formatted version of the article will be published soon.

Abstract Background: Exosome-hydrogel complexes have great potential in regenerative medicine, being able to combine biological signals with structural support. But overall, the knowledge structure and translational connections between academic discoveries and patent deployment are not clear. Methods: A dual-source analysis framework was established to analyze academic papers and patents, illustrating the landscape of exosome–hydrogel research from 2016 to 2025. An interdisciplinary knowledge graph was constructed using topic modeling, entity–relation extraction, and evidence-ranking methods to quantify temporal trends, thematic differences, and translational gaps. Results: The core components include mesenchymal stem cell–derived exosomes and hydrogels based on gelatin methacrylate (GelMA) or collagen, which form a well-established research foundation. Academic research focuses on osteogenesis, and recent progress mentions angiogenesis and immune regulation. The research application has strong temperature dependence, and patent activities lag behind academic publications. Several high-evidence yet unpatented propositions, such as "hydrogel-encapsulated exosomes" and "exosome-enhanced angiogenesis," represent potential innovation opportunities. Conclusion: This study employs a data-driven framework to connect scientific research with transformation. The integration of semantic models and cross - source evidence reflects the evaluation logic of exosome - hydrogel research, and provides support for future research in the field of regenerative biomaterials and the priority of patent strategies.

Keywords: artificial intelligence, big data analytics, Bone Regeneration and Tissue Engineering, Exosome–Hydrogel Systems, knowledge graph

Received: 12 Jan 2026; Accepted: 26 Jan 2026.

Copyright: © 2026 Li, Lou, Wang and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Minglei Zhang

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