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FODS '20 : proceedings of the 2020 ACM-IMS Foundations of Data Science Conference : October 19-20, 2020, Virtual Event, USA. ACM-IMS Foundations of Data Science Conference (2020 : Online)最新文献

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AutoML and Interpretability: Powering the Machine Learning Revolution in Healthcare 自动化和可解释性:推动医疗保健领域的机器学习革命
M. Schaar
An AutoML and interpretability are both fundamental to the successful uptake of machine learning by non-expert end users. The former will lower barriers to entry and unlock potent new capabilities that are out of reach when working with ad-hoc models, while the latter will ensure that outputs are transparent, trustworthy, and meaningful. In healthcare, AutoML and interpretability are already beginning to empower the clinical community by enabling the crafting of actionable analytics that can inform and improve decision-making by clinicians, administrators, researchers, policymakers, and beyond. This keynote presents state-of-the-art AutoML and interpretability methods for healthcare developed in our lab and how they have been applied in various clinical settings (including cancer, cardiovascular disease, cystic fibrosis, and recently Covid-19), and then explains how these approaches form part of a broader vision for the future of machine learning in healthcare.
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引用次数: 2
FODS '20: ACM-IMS Foundations of Data Science Conference, Virtual Event, USA, October 19-20, 2020 FODS '20: ACM-IMS数据科学基础会议,虚拟事件,美国,2020年10月19-20日
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引用次数: 2
期刊
FODS '20 : proceedings of the 2020 ACM-IMS Foundations of Data Science Conference : October 19-20, 2020, Virtual Event, USA. ACM-IMS Foundations of Data Science Conference (2020 : Online)
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