Integrating AI Tools and Strategies Into Medical Writing: A Hands-On Workshop With Núria Negrão, PhD

In the next 2 to 3 years, AI will revolutionize the field of medical writing by offering improved accuracy, faster turnaround times, and enhanced creativity. For example, AI can assist with idea generation, literature reviews, interpreting statistical results, and summarizing articles.

Large Language Models (LLMs) play a central role in AI tools. These models predict the next tokens in a sequence based on the context of the writing. Trained on extensive datasets, LLMs leverage deep learning to continually enhance their predictive capabilities. When a medical writer collaborates with an AI trained on LLMs, the AI proves invaluable in facilitating patient communication by translating complex professional terminology into plain language and structuring information in a clear, patient-friendly manner. However, LLMs still have limitations, such as potential HIPAA violations and the risk of providing outdated information due to memory constraints or inadequate training.

Despite these shortcomings, LLM-trained AI tools offer significant benefits to medical writers. They can save time on language processing tasks like summarizing and outlining published articles, organizing comments into comprehensive drafts, and generating meeting notes. A workbook comparison of three AI tools—ChatGPT, Gemini, and Copilot—highlights their unique strengths and applications in enhancing medical writing workflows.