In January 2025, DeepSeek launched its reasoning model DeepSeek-R1, characterized by open-source accessibility, cost-effectiveness, and strong reasoning capabilities, thus showing significant potential for applications within the medical domain. This paper examines the prospects for DeepSeek's implementation in general practice, demonstrating its potential to support clinical decision-making at primary care levels, facilitate comprehensive health education and management throughout the healthcare lifecycle, and bridge service gaps in remote, impoverished, and underserved regions. Additionally, DeepSeek-R1 enables to enhance research efficiency and promote innovative modes of medical education and training. However, its deployment also faces challenges concerning data governance, ethical standards, and technical specifications. Future exploration is recommended to facilitate the deep integration of large language models such as DeepSeek into multiple dimensions of general practitioners' activities-including clinical practice, scientific research, and medical education-thus maximizing the empowering role of artificial intelligence in general practice, developing an intelligent primary care ecosystem, and promoting high-quality development in general medicine.

2025年1月，DeepSeek推出推理模型DeepSeek-R1，其凭借开源、成本效益高、推理能力强等优势，在医疗领域应用前景广阔。本文深入探讨DeepSeek在全科医学中的应用前景，得出其能辅助基层诊疗决策、支持全周期健康教育与管理、填补"老少边穷"地区服务缺口，还可提升科研效率、助力教学培训模式创新。不过，其应用面临数据治理、伦理规范、技术标准等挑战。未来，建议探索推动DeekSeek等大语言模型辅助全科医生在医疗实践、科学研究、教学培训等多维服务场景的深度融合，更好地发挥人工智能赋能全科医学的作用，构建智慧全科生态体系，促进全科医学高质量发展。