Global trends in AI applications for retinal disease diagnosis
A recent bibliometric study highlights significant advancements and trends in artificial intelligence (AI) research within retinal disease over the past decade. Analyzing 2,861 articles from 93 countries between 2014 and 2023, the study underscores growing global interest and collaboration in this field, particularly since 2017.
China leads in publication volume with 926 articles, accounting for 32% of the total, while the United States demonstrates the greatest research impact with an h-index of 66. England appears the best at fostering collaborative networks, with key contributions from the University of London and University College London, each producing 99 articles and achieving an h-index of 25. The National University of Singapore is also a central figure in promoting global research partnerships.
Key research areas include ophthalmology and computer science, with diabetic retinopathy as the most extensively studied condition. Recent advancements focus on “transfer learning,” “convolutional neural networks,” and similar algorithms aimed at diagnosing retinal diseases and analyzing abnormal eye features.
The study calls for future efforts to develop more sophisticated diagnostic systems to address broader ophthalmic challenges.
Reference
Guo M, Gong D, Yang W. In-depth analysis of research hotspots and emerging trends in AI for retinal diseases over the past decade. Front Med (Lausanne). 2024;11:1489139. doi: 10.3389/fmed.2024.1489139. PMID: 39635592; PMCID: PMC11614663.
