Generative artificial intelligence in ophthalmology research writing: A comprehensive review of applications, detection tools, and ethical considerations

Abstract

Abstract: The rise of generative artificial intelligence (GenAI) has profoundly influenced medical research and academic writing, particularly in ophthalmology. Despite its growing relevance, there is a noticeable gap in the literature regarding its application in medical writing, including practical uses and associated limitations. This review seeks to fill in this gap by first systematically reviewing the current literature on GenAI in medical paper writing. It identifies and discusses nine key applications and considerations, including idea generation, literature review, institutional review board preparation, data collection, data analysis, image generation, manuscript drafting, writing refinement, and peer review. In the second part, we explore publicly available AI tools that currently assist with medical manuscript writing. We also introduce several generative AI detection tools and discuss their accuracy and reliability. Finally, the review addresses the limitations and ethical challenges associated with the use of GenAI in medical paper writing. While GenAI has streamlined many aspects of medical paper writing, and an increasing number of AI tools have been developed for research, significant model limitations and ethical concerns persist, necessitating careful human oversight and clear guidelines. By providing a comprehensive yet focused overview, this article offers valuable insights into the effective use of GenAI in medical paper writing while acknowledging its limitations and risks. It aims to support researchers in producing high-quality, AI-enhanced publications in the field of ophthalmology.

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