Developing medical imaging AI for emerging infectious diseases.
Developing medical imaging AI for emerging infectious diseases.
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DOI：
10.1038/s41467-022-34234-4
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发表时间：
2022-11-18
影响因子：
16.6
通讯作者：
中科院分区：
文献类型：
--
作者：
人工智能（AI）和计算机视觉的进步为协助医务人员、优化医疗工作流程和改善患者预后带来了巨大希望。COVID-19大流行给世界各地的医疗系统造成了前所未有的压力，这似乎是人工智能展示其有用性的绝佳机会。然而，在为COVID-19开发的数百种医学成像AI模型中，很少有适合在现实世界中部署的模型，有些模型可能是有害的。该综述旨在检查先前研究的优点和缺点，并为构建有用的医学成像AI模型的不同阶段提供建议，其中包括：需求发现，数据集管理，模型开发和评估以及部署后的考虑因素。此外，本文还总结了经验教训，以告知科学界如何在未来的大流行中创建有用的医学成像AI。很少有COVID-19 ML模型适合在现实世界中部署。在这篇评论中，Huang等人讨论了在新兴传染病的背景下开发临床有用模型所需的主要步骤。
Advances in artificial intelligence (AI) and computer vision hold great promise for assisting medical staff, optimizing healthcare workflow, and improving patient outcomes. The COVID-19 pandemic, which caused unprecedented stress on healthcare systems around the world, presented what seems to be a perfect opportunity for AI to demonstrate its usefulness. However, of the several hundred medical imaging AI models developed for COVID-19, very few were fit for deployment in real-world settings, and some were potentially harmful. This review aims to examine the strengths and weaknesses of prior studies and provide recommendations for different stages of building useful AI models for medical imaging, among them: needfinding, dataset curation, model development and evaluation, and post-deployment considerations. In addition, this review summarizes the lessons learned to inform the scientific community about ways to create useful medical imaging AI in a future pandemic. Very few of the COVID-19 ML models were fit for deployment in real-world settings. In this Comment, Huang et al. discuss the main steps required to develop clinically useful models in the context of an emerging infectious disease.
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影响因子：
7.7
作者：
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影响因子：
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DOI：
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发表时间：
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期刊：
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