Leveraging Artificial Intelligence in Anesthesiology Research and Article Writing: Opportunities, Challenges, and Best Practices

Conducting and reporting scientific research in anesthesiology involves a complex, detailed process. From conducting literature reviews to formulating hypotheses and executing robust statistical analyses, anesthesiology research demands extreme accuracy and fidelity. The dual nature of anesthesiology research, bridging basic science and clinical practice, underscores the need for precise and nuanced planning and reporting in scientific writing. Artificial intelligence (AI) tools such as ChatGPT, Julius AI, and Notebook LM can support various stages of anesthesiology research, enhancing efficiency in tasks like literature review, statistical analysis, and article drafting. However, their use requires careful oversight to preserve data integrity and to avoid common pitfalls, such as AI-generated “hallucinations” or inappropriate language model drift. These risks underscore the importance of guiding anesthesiologists in the responsible use of AI for study design and scientific reporting. Practical applications include literature reviews, statistical planning and analyses, data visualization, and language refinement, with an emphasis on safeguarding scientific rigor and enhancing research quality in anesthesiology publications. Health Insurance Portability and Accountability Act (HIPAA) consent does not apply to this article. This article provides a practical framework for anesthesiologists to integrate AI tools into research and article writing while maintaining scientific rigor. It uniquely contributes to the field by outlining specific use cases, tool comparisons, and ethical considerations tailored to the needs of anesthesiology, offering guidance on responsible AI use in literature reviews, statistical analysis, and reporting.