标题： 非洲数据稀缺的挑战：一种增加本地数据收集和整合的建议 显示英文标题

标题： Themed Challenges to Solve Data Scarcity in Africa: A Proposition for Increasing Local Data Collection and Integration

摘要： 在非洲，计算资源和医疗数据集的匮乏仍然是人工智能（AI）工具在临床环境中开发和部署的主要障碍，进一步加剧了全球偏见。 这些限制阻碍了人工智能潜力的充分发挥，并对推动该地区医疗保健的发展构成了严重挑战。 本文提出了一种框架，旨在解决非洲医疗保健中的数据稀缺问题。 该框架提出了一个全面的策略，以鼓励整个大陆的医疗机构创建、整理和共享本地获取的医学影像数据集。 通过组织促进参与的主题挑战，可以在非洲医疗保健社区内生成准确且相关的数据集。 这种方法旨在克服现有的数据集限制，为一个更加包容且具有影响力的AI生态系统铺平道路，该系统专门针对非洲的医疗需求进行定制。 显示英文摘要

摘要： In Africa, the scarcity of computational resources and medical datasets remains a major hurdle to the development and deployment of artificial intelligence (AI) tools in clinical settings, further contributing to global bias. These limitations hinder the full realization of AI's potential and present serious challenges to advancing healthcare across the region. This paper proposes a framework aimed at addressing data scarcity in African healthcare. The framework presents a comprehensive strategy to encourage healthcare providers across the continent to create, curate, and share locally sourced medical imaging datasets. By organizing themed challenges that promote participation, accurate and relevant datasets can be generated within the African healthcare community. This approach seeks to overcome existing dataset limitations, paving the way for a more inclusive and impactful AI ecosystem that is specifically tailored to Africa's healthcare needs.