Healthcare is one of the most promising areas for machine learning models to make a positive impact. However, successful adoption of AI-based systems in healthcare depends on engaging and educating stakeholders from diverse backgrounds about the development process of AI models. We present a broadly accessible overview of the development life cycle of clinical AI models that is general enough to be adapted to most machine learning projects, and then give an in-depth case study of the development process of a deep learning based system to detect aortic aneurysms in Computed Tomography (CT) exams. We hope other healthcare institutions and clinical practitioners find the insights we share about the development process useful in informing their own model development efforts and to increase the likelihood of successful deployment and integration of AI in healthcare.

中文翻译：

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医疗保健系统临床 AI 模型开发生命周期的概述和案例研究

医疗保健是机器学习模型最有希望产生积极影响的领域之一。然而，在医疗保健中成功采用基于人工智能的系统取决于让来自不同背景的利益相关者参与和教育人工智能模型的开发过程。我们对临床 AI 模型的开发生命周期进行了广泛的概述，该概述足以适应大多数机器学习项目，然后对基于深度学习的系统的开发过程进行深入的案例研究，以检测主动脉计算机断层扫描 (CT) 检查中的动脉瘤。