基于非洲天然产物的大语言模型在重度抑郁症支持中的应用
The Application of Large Language Models on Major Depressive Disorder Support Based on African Natural Products
AI总结：
本文研究将大语言模型与非洲天然产物相结合用于重度抑郁症支持，通过分析非洲药用植物的抗抑郁特性与药理机制，构建基于DeepSeek的AI支持系统，以弥合传统知识与现代医疗之间的鸿沟。
摘要：
重度抑郁症是21世纪最重大的全球健康挑战之一，影响全球数百万人，并造成巨大的经济和社会负担。虽然传统抗抑郁疗法已为许多个体提供了缓解，但其局限性——包括起效延迟、显著副作用以及相当一部分患者存在治疗抵抗——促使研究者和医疗提供者探索替代性治疗方法（Kasneci et al.）。非洲传统医学拥有数千年发展而来的丰富植物疗法遗产，为开发可能解决其中部分局限性的新型抗抑郁治疗提供了宝贵资源。本文探讨了大语言模型与非洲天然产物在抑郁症支持中的整合，将传统知识与现代人工智能技术相结合，以构建可及、循证的心理健康支持系统。本文所呈现的研究涵盖了对具有文献记载抗抑郁特性的非洲药用植物的全面分析、其药理机制，以及一个利用DeepSeek先进语言模型能力开发的AI驱动支持系统。该系统提供关于非洲草药、其临床应用、安全性考量和治疗方案等方面的循证信息，同时保持科学严谨性和适当的安全标准。我们的研究结果表明，大语言模型有潜力充当传统知识与现代医疗之间的桥梁，提供个性化、文化适配的抑郁症支持，既尊重传统智慧，也尊重当代医学理解。
英文摘要：
Major depressive disorder represents one of the most significant global health challenges of the 21st century, affecting millions of people worldwide and creating substantial economic and social burdens. While conventional antidepressant therapies have provided relief for many individuals, their limitations including delayed onset of action, significant side effects, and treatment resistance in a substantial portion of patients have prompted researchers and healthcare providers to explore alternative therapeutic approaches (Kasneci et al.). African traditional medicine, with its rich heritage of plant-based remedies developed over millennia, offers a valuable resource for developing novel antidepressant treatments that may address some of these limitations. This paper examines the integration of large language models with African natural products for depression support, combining traditional knowledge with modern artificial intelligence technology to create accessible, evidence-based mental health support systems. The research presented here encompasses a comprehensive analysis of African medicinal plants with documented antidepressant properties, their pharmacological mechanisms, and the development of an AI-powered support system that leverages DeepSeek's advanced language model capabilities. The system provides evidence-based information about African herbal medicines, their clinical applications, safety considerations, and therapeutic protocols while maintaining scientific rigor and appropriate safety standards. Our findings demonstrate the potential for large language models to serve as bridges between traditional knowledge and modern healthcare, offering personalized, culturally appropriate depression support that honors both traditional wisdom and contemporary medical understanding.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
