ChatGPT Surpasses 1000 Publications on PubMed: Envisioning the Road Ahead

Abstract

The exponential growth of ChatGPT in medical literature, amassing over 1000 PubMed citations by August 2023, underscores a pivotal juncture in the convergence of artificial intelligence (AI) and healthcare. This remarkable rise not only showcases its potential to revolutionize medical academia but also indicates its impending influence on patient care and healthcare systems. Notwithstanding this enthusiasm, one-third of these citations are editorials or commentaries, stressing a gap in empirical research. Alongside its potential, there are concerns about ChatGPT becoming a "Weapon of Mass Deception" and the need for rigorous evaluations to counter inaccuracies. The World Association of Medical Editors has released guidelines emphasizing that AI tools should not be manuscript co-authors and advocates for clear disclosures in AI-assisted academic works. Interestingly, ChatGPT achieved its citation milestone within nine months, compared to Google's 14 years. As Large Language Models (LLMs), like ChatGPT, become more integral in healthcare, issues surrounding data protection, patient privacy, and ethical implications gain prominence. As the future of LLM research unfolds, key areas of interest include its efficacy in clinical settings, its role in telemedicine, and its potential in medical education. The journey ahead necessitates a harmonious partnership between the medical community and AI developers, emphasizing both technological advancements and ethical considerations. Categories: Public Health, Healthcare Technology Keywords: published in pubmed journal, randomized controlled trial (rct), ai chatbot, ethical implications, medical education, telemedicine, artificial intelligence (ai), llms in healthcare, pubmed, chatgpt Editorial The rapid rise of ChatGPT (Chat Generative Pre-trained Transformer) in medical literature, with over 1000 PubMed citations by August 2023 (Figure 1), signals a critical moment in blending artificial intelligence (AI) and healthcare. This "new" large language model (LLM) illustrated vast prospects for transforming medical academia and, potentially, healthcare practices. Its influence may soon extend beyond research to practical applications, reshaping patient care and healthcare systems. However, of these PubMed citations, a notable one-third are editorials or commentaries, highlighting the need for more empirical studies.