In recent years, the application of large language models (LLM) in medical research has rapidly expanded, covering a wide range of critical areas such as clinical question-answering, diagnostic assistance, and medical record generation. However, conducting such research not only requires adherence to the fundamental principles of traditional clinical epidemiology but also must meet the unique methodological demands of artificial intelligence technologies. To this end, this article systematically summarizes key aspects of LLM-based medical research, including study design, measurement metrics, methodological quality assessment, and reporting standards, aiming to provide methodological support for medical researchers and facilitate the more standardized and efficient application of LLM technology in medical practice and scientific innovation.