Barts and the London Medical School, Queen Mary University of London, London, United Kingdom.
Department of Medical Education, Brighton and Sussex Medical School, University of Brighton, Brighton, United Kingdom.
J Med Eng Technol. 2021 Jan;45(1):75-80. doi: 10.1080/03091902.2020.1853839. Epub 2020 Dec 7.
It is estimated that missed opportunities for diagnosis occur in 1 in 20 primary care appointments. This is not only detrimental to individual patients, but also to the healthcare system as health outcomes are affected and healthcare expenditure inevitably increases. There are many potential solutions to limit the number of missed opportunities for diagnosis and management, one of which is through the use of artificial intelligence. Artificial intelligence and machine learning research and capabilities have exponentially grown in the past decades, with their applications in medicine showing great promise. As such, this review aims to discuss the possible uses of machine learning in primary care to maximise the quality of care provided.
据估计，20 次初级保健就诊中就有 1 次会错失诊断机会。这不仅对个体患者不利，而且对医疗保健系统也不利，因为会影响健康结果，从而不可避免地增加医疗保健支出。有许多潜在的解决方案可以限制错失诊断和管理的机会，其中之一是通过使用人工智能。在过去几十年中，人工智能和机器学习的研究和能力呈指数级增长，其在医学中的应用前景广阔。因此，本文旨在讨论机器学习在初级保健中的可能用途，以最大限度地提高所提供的护理质量。
