Recent advancements in generative artificial intelligence, particularly using large language models (LLMs), are gaining increased public attention. We provide a perspective on the potential of LLMs to analyze enormous amounts of data from medical records and gain insights on specific topics in neurology. In addition, we explore use cases for LLMs, such as early diagnosis, supporting patient and caregivers, and acting as an assistant for clinicians. We point to the potential ethical and technical challenges raised by LLMs, such as concerns about privacy and data security, potential biases in the data for model training, and the need for careful validation of results. Researchers must consider these challenges and take steps to address them to ensure that their work is conducted in a safe and responsible manner. Despite these challenges, LLMs offer promising opportunities for improving care and treatment of various neurologic disorders.

生成人工智能的最新进展，特别是使用大型语言模型（LLM），正在引起公众越来越多的关注。我们提供了关于法学硕士分析大量医疗记录数据并获得对神经病学特定主题的见解的潜力的观点。此外，我们还探索法学硕士的用例，例如早期诊断、支持患者和护理人员以及充当临床医生的助手。我们指出了法学硕士提出的潜在道德和技术挑战，例如对隐私和数据安全的担忧、模型训练数据的潜在偏差以及仔细验证结果的需要。研究人员必须考虑这些挑战并采取措施应对这些挑战，以确保他们的工作以安全和负责任的方式进行。尽管存在这些挑战，法学硕士为改善各种神经系统疾病的护理和治疗提供了有希望的机会。