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Machine Learning for Pulmonary and Critical Care Medicine: A Narrative Review

机译：肺部和关键护理机器学习：叙事评论

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摘要

Machine learning (ML) is a discipline of computer science in which statistical methods are applied to data in order to classify, predict, or optimize, based on previously observed data. Pulmonary and critical care medicine have seen a surge in the application of this methodology, potentially delivering improvements in our ability to diagnose, treat, and better understand a multitude of disease states. Here we review the literature and provide a detailed overview of the recent advances in ML as applied to these areas of medicine. In addition, we discuss both the significant benefits of this work as well as the challenges in the implementation and acceptance of this non-traditional methodology for clinical purposes.
机译：机器学习（ML）是计算机科学的学科，其中统计方法应用于数据，以基于先前观察到的数据来分类，预测或优化。肺部和关键护理医学在这种方法中看到了激增，潜在地提供改善我们诊断，治疗和更好地了解众多疾病状态的能力。在这里，我们审查了文献，并详细概述了ML的最近进步，适用于这些医学领域。此外，我们讨论了这项工作的重要利益以及对临床目的的非传统方法的实施和接受的挑战。

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