AIAIAI: AI insights on amassing influence in AI-related publications - an AI-assisted retrospective analysis into AI-related publication.

Abstract

Objectives: This study analyses the trend of artificial intelligence (AI)-related publications in the medical field over the past decade and demonstrates the potential of AI in automating data analysis. We hypothesise exponential growth in AI-related publications, with continuous growth in the foreseeable future.

Methods: Retrospective, AI-assisted analysis was conducted using the OpenAI application programming interface for data collection and evaluation. Publications from the top 50 medical journals (Web of Science, Journal Citation Report, 2022) covering 2014 to June 2024. A total of 315 209 papers were initially retrieved with 212 620 remaining after filtering. The outcomes were the total number and percentage of AI-related publications per year, with future trends prediction using statistical models.

Results: AI-related publications increased from approximately 500 in 2014 to over 1000 in 2022, with the percentage rising from 2.5% to over 6% in 2024. The analysis identified cardiology and oncology as leading in AI adoption. Predictive models forecast that AI-related publications could reach 10% by 2030 with long-term projections suggesting potential dominance of AI presence by the mid-22nd century.

Discussion: The study highlights the significant growth and integration of AI in medical research, with cardiology and oncology at the forefront. AI-assisted data analysis proves efficient and scalable but requires human oversight to maintain credibility.

Conclusions: The trajectory of AI-related publications indicates substantial growth and future integration across medical disciplines. Ongoing evaluation of AI's reliability and applicability in medical research remains essential.