The International Centre for Eye Health (ICEH), London School of Hygiene and Tropical Medicine, London, United Kingdom.
Peek Vision, London, United Kingdom.
Front Public Health. 2021 Dec 22;9:752049. doi: 10.3389/fpubh.2021.752049. eCollection 2021.
Achieving The United Nations sustainable developments goals by 2030 will be a challenge. Researchers around the world are working toward this aim across the breadth of healthcare. Technology, and more especially artificial intelligence, has the ability to propel us forwards and support these goals but requires careful application. Artificial intelligence shows promise within healthcare and there has been fast development in ophthalmology, cardiology, diabetes, and oncology. Healthcare is starting to learn from commercial industry leaders who utilize fast and continuous testing algorithms to gain efficiency and find the optimum solutions. This article provides examples of how commercial industry is benefitting from utilizing AI and improving service delivery. The article then provides a specific example in eye health on how machine learning algorithms can be purposed to drive service delivery in a resource-limited setting by utilizing the novel study designs in response adaptive randomization. We then aim to provide six key considerations for researchers who wish to begin working with AI technology which include collaboration, adopting a fast-fail culture and developing a capacity in ethics and data science.
到 2030 年实现联合国可持续发展目标将是一项挑战。世界各地的研究人员正在医疗保健、技术等各个领域朝着这一目标努力。人工智能具有推动我们前进和支持这些目标的能力,但需要谨慎应用。人工智能在医疗保健领域显示出巨大的潜力,在眼科、心脏病学、糖尿病和肿瘤学等领域取得了快速发展。医疗保健行业开始向商业行业领导者学习,这些领导者利用快速和持续的测试算法来提高效率并找到最佳解决方案。本文提供了一些例子,说明商业行业如何从利用人工智能中受益,并提高服务交付水平。然后,本文在眼健康方面提供了一个具体的例子,说明如何通过利用响应适应性随机化的新型研究设计,利用机器学习算法来推动资源有限环境下的服务交付。然后,我们旨在为希望开始使用人工智能技术的研究人员提供六个关键考虑因素,包括合作、采用快速失败文化以及在伦理和数据科学方面培养能力。