# Global trends and hotspots in artificial intelligence for high myopia: a bibliometric analysis

## TL;DR

This paper analyzes global research trends in using artificial intelligence for high myopia, highlighting growth and key contributors since 2017.

## Contribution

The study provides the first comprehensive bibliometric analysis of AI applications in high myopia research.

## Key findings

- China is the most productive country in AI-related high myopia research with strong international collaboration.
- Retinal imaging remains a central focus, while 'automated detection' and 'childhood' are emerging keywords.
- Yang, Weihua and Investigative Ophthalmology & Visual Science are the top contributors in publications.

## Abstract

This study aims to conduct a bibliometric analysis of global publications on the application of artificial intelligence (AI) in high myopia (HM).

We retrieved publications on AI in HM from the Web of Science Core Collection (WoSCC) database, MEDLINE and Chinese Science Citation Database (CSCD) with data up to 2024. The analysis focused on publication and citation trends, identifying key articles, influential countries, institutions, authors, and journals. Additionally, we explored research domains and emerging keywords.

A total of 167 relevant publications were included. The first AI-related paper on HM was published in 2017, with a significant surge in 2021, followed by a consistent increase in publication and citation counts over the next 3 years. China emerged as the most productive country, with the most extensive international collaboration. East Asian authors dominated the top 10 most influential authors. Yang, Weihua and Investigative Ophthalmology & Visual Science (IOVS) contributed the most publications among authors and institutions, respectively. Keyword analysis revealed that retinal imaging-related terms remained a consistent research focus, while newly emerging keywords included “automated detection” and “childhood.”

Recent advancements in AI applications for HM have been significant and are expected to continue. Future research will likely focus on multimodal imaging and improving algorithm accessibility. Our findings offered the first comprehensive overview of global research on AI in HM, thus providing valuable insights for researchers to understand the current status and future trends in this field.