Bergling Karin, Wang Lin-Chun, Shivakumar Oshini, Nandorine Ban Andrea, Moore Linda W, Ginsberg Nancy, Kooman Jeroen, Duncan Neill, Kotanko Peter, Zhang Hanjie
Artificial Intelligence Translational Innovation Hub, Renal Research Institute, New York, NY, USA.
Fresenius Medical Care, Clinical Research, New York, NY, USA.
Clin Kidney J. 2025 Mar 17;18(4):sfaf082. doi: 10.1093/ckj/sfaf082. eCollection 2025 Apr.
Large language models (LLMs) such as ChatGPT are increasingly positioned to be integrated into various aspects of daily life, with promising applications in healthcare, including personalized nutritional guidance for patients with chronic kidney disease (CKD). However, for LLM-powered nutrition support tools to reach their full potential, active collaboration of healthcare professionals, patients, caregivers and LLM experts is crucial. We conducted a comprehensive review of the literature on the use of LLMs as tools to enhance nutrition recommendations for patients with CKD, curated by our expertise in the field. Additionally, we considered relevant findings from adjacent fields, including diabetes and obesity management. Currently, the application of LLMs for CKD-specific nutrition support remains limited and has room for improvement. Although LLMs can generate recipe ideas, their nutritional analyses often underestimate critical food components such as electrolytes and calories. Anticipated advancements in LLMs and other generative artificial intelligence (AI) technologies are expected to enhance these capabilities, potentially enabling accurate nutritional analysis, the generation of visual aids for cooking and identification of kidney-healthy options in restaurants. While LLM-based nutritional support for patients with CKD is still in its early stages, rapid advancements are expected in the near future. Engagement from the CKD community, including healthcare professionals, patients and caregivers, will be essential to harness AI-driven improvements in nutritional care with a balanced perspective that is both critical and optimistic.
诸如ChatGPT之类的大语言模型（LLMs）越来越多地被定位为融入日常生活的各个方面，在医疗保健领域有着广阔的应用前景，包括为慢性肾脏病（CKD）患者提供个性化营养指导。然而，要使基于大语言模型的营养支持工具发挥其全部潜力，医疗保健专业人员、患者、护理人员和大语言模型专家的积极合作至关重要。我们凭借在该领域的专业知识，对有关使用大语言模型作为增强CKD患者营养建议工具的文献进行了全面综述。此外，我们还考虑了相邻领域的相关研究结果，包括糖尿病和肥胖管理。目前，大语言模型在CKD特异性营养支持方面的应用仍然有限，还有改进的空间。虽然大语言模型可以生成食谱创意，但其营养分析往往低估了关键食物成分，如电解质和卡路里。预计大语言模型和其他生成式人工智能（AI）技术的进步将增强这些能力，有可能实现准确的营养分析、生成烹饪视觉辅助工具以及识别餐厅中有益于肾脏健康的菜品。虽然基于大语言模型的CKD患者营养支持仍处于早期阶段，但预计在不久的将来会有快速进展。CKD群体（包括医疗保健专业人员、患者和护理人员）的参与对于以既批判性又乐观的平衡视角利用人工智能驱动的营养护理改进至关重要。
