Ever feel lost in a sea of medical jargon after a doctor's appointment? You're not alone. Electronic Health Records (EHRs) are packed with complex medical terms, often leaving patients confused and struggling to understand their own health information. But what if AI could help bridge this communication gap? New research explores how large language models (LLMs), like the technology behind ChatGPT, can be used to extract and explain medical jargon tailored to individual patient demographics. Imagine an AI that understands your age, education level, and even how frequently you read health materials. This AI could then identify the specific medical terms *you* are likely to find confusing and either avoid using them or offer simple definitions. Researchers tested this concept by having an LLM "role-play" different demographic groups and extract medical jargon from real EHR sentences. They found that when the AI took on the persona of specific demographics, its ability to identify potentially confusing jargon improved. This opens exciting doors for personalized patient education. Think of EHR notes that automatically adjust their language to your comprehension level or chatbot-based self-diagnosis tools that speak your language. While more research is needed—the initial tests were done on a limited number of sentences—this innovative use of LLMs promises a future where medical information is clear, accessible, and empowers everyone to take control of their health.