Background <p>Artificial intelligence has gained broad applications in stem cell research, becoming a core technology in regenerative medicine, cancer stem cells, and cell therapy. Due to the wide scope of this domain, most studies have considered artificial intelligence’s use within a particular subfield or provided a scoping review of a particular subfield of stem cell science. However, none have provided a comprehensive analysis of artificial intelligence integration into stem cell research from its earliest evolution in the 1990s to the present.</p> Main body <p>This research analyzes the current direction and pace of artificial intelligence integration across all aspects of stem cell research from 1994 to 2025, while highlighting future directions and prospects. To achieve this, the study retrieved 4,712 documents from Scopus. All articles were subjected to PRISMA eligibility criteria, and 2,866 articles were retained and analyzed. Results showed that 63% of research on artificial intelligence’s use in stem cell studies were research articles with an annual growth rate of 20% and an average of 15 citations. This double-digit growth rate indicates that studies on artificial intelligence and stem cells are growing exponentially, with the USA, China, Japan, Germany, and the UK leading in publications. The most productive researcher is “Wang Y,” while “Li Y” emerged as the most impactful author. Meanwhile, cross-country collaborations are low, fragmented, and propelled mostly by regional, financial, and/or economic interests.</p> Conclusions <p>Future trends in stem cell research point towards the use of artificial intelligence for precision medicine, tumor microenvironment analysis, understanding heterogeneity, and organoid development. This study offers useful insights into the trends in artificial intelligence integration in stem cell research and provides researchers with useful guidance for further exploration of this domain.</p> Clinical trial number <p>Not applicable.</p>

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Integration of artificial intelligence in stem cell research: a comprehensive bibliometric and emerging trend analysis

  • Israel Ogwuche Ogra,
  • Oluwatimileyin Deborah Obasa,
  • Jeremiah Zaphnathpaaneah Adaji,
  • Samson Usman,
  • Daniel Thakuma Tizhe,
  • Precious Ezinne Nebo,
  • Faustina Ntim Opoku,
  • Shadrack Dangabar Apollos,
  • David John Burman Ladan,
  • Nsuhoridem Aniekan Johnson,
  • Emmanuel Oluwadare Balogun,
  • Kodjovi Sossou

摘要

Background

Artificial intelligence has gained broad applications in stem cell research, becoming a core technology in regenerative medicine, cancer stem cells, and cell therapy. Due to the wide scope of this domain, most studies have considered artificial intelligence’s use within a particular subfield or provided a scoping review of a particular subfield of stem cell science. However, none have provided a comprehensive analysis of artificial intelligence integration into stem cell research from its earliest evolution in the 1990s to the present.

Main body

This research analyzes the current direction and pace of artificial intelligence integration across all aspects of stem cell research from 1994 to 2025, while highlighting future directions and prospects. To achieve this, the study retrieved 4,712 documents from Scopus. All articles were subjected to PRISMA eligibility criteria, and 2,866 articles were retained and analyzed. Results showed that 63% of research on artificial intelligence’s use in stem cell studies were research articles with an annual growth rate of 20% and an average of 15 citations. This double-digit growth rate indicates that studies on artificial intelligence and stem cells are growing exponentially, with the USA, China, Japan, Germany, and the UK leading in publications. The most productive researcher is “Wang Y,” while “Li Y” emerged as the most impactful author. Meanwhile, cross-country collaborations are low, fragmented, and propelled mostly by regional, financial, and/or economic interests.

Conclusions

Future trends in stem cell research point towards the use of artificial intelligence for precision medicine, tumor microenvironment analysis, understanding heterogeneity, and organoid development. This study offers useful insights into the trends in artificial intelligence integration in stem cell research and provides researchers with useful guidance for further exploration of this domain.

Clinical trial number

Not applicable.