将机器学习应用于医疗保健的现实世界:外部验证、持续监控和随机临床试验。

Han Yuan
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引用次数: 0

摘要

在这篇评论中,我们阐明了在医疗保健领域实际部署机器学习不可或缺的三个评估步骤,并展示了诊断、治疗和预后任务的可参考示例。我们鼓励研究人员超越回顾性验证和样本内验证,在床边进行实际应用,而不是将开发的机器学习模型尘封在存档文献中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Toward real-world deployment of machine learning for health care: External validation, continual monitoring, and randomized clinical trials

Toward real-world deployment of machine learning for health care: External validation, continual monitoring, and randomized clinical trials

In this commentary, we elucidate three indispensable evaluation steps toward the real-world deployment of machine learning within the healthcare sector and demonstrate referable examples for diagnostic, therapeutic, and prognostic tasks. We encourage researchers to move beyond retrospective and within-sample validation, and step into the practical implementation at the bedside rather than leaving developed machine learning models in the dust of archived literature.

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