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Estimate the hidden deployment cost of predictive models to improve patient care.
Nature Medicine ( IF 82.9 ) Pub Date : 2020-01-01 , DOI: 10.1038/s41591-019-0651-8
Keith E Morse 1, 2 , Steven C Bagley 3 , Nigam H Shah 3
Affiliation  

Although examples of algorithms designed to improve healthcare delivery abound, for many, clinical integration will not be achieved. The deployment cost of machine learning models is an underappreciated barrier to success. Experts propose three criteria that, assessed early, could help estimate the deployment cost.

中文翻译:

估算预测模型以改善患者护理的隐藏部署成本。

尽管为改善医疗保健服务而设计的算法示例比比皆是,但对于许多人来说,临床集成将无法实现。机器学习模型的部署成本是成功被忽视的障碍。专家提出了三个标准,这些标准可以尽早评估,有助于评估部署成本。
更新日期:2020-01-14
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