Enabling Machine Learning in Critical Care.

ICU management & practice Pub Date : 2017-01-01
Tom J Pollard, Leo Anthony Celi
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Abstract

Critical care units are home to some of the most sophisticated patient technology within hospitals. In parallel, the field of machine learning is advancing rapidly and increasingly touching our lives. To facilitate the adoption of machine learning approaches in critical care, we must become better at sharing and integrating data. Greater emphasis on collaboration- outside the traditional "multidisciplinary" realm and into the engineering, mathematical, and computer sciences-will help us to achieve this. Meanwhile, those at the forefront of the health data revolution must earn and maintain society's trust and demonstrate that data sharing and reuse is a necessary step to improve patient care.

在重症监护中实现机器学习。
重症监护病房是医院中一些最先进的病人技术的所在地。与此同时,机器学习领域正在迅速发展,并越来越多地影响我们的生活。为了促进在重症监护中采用机器学习方法,我们必须更好地共享和整合数据。更强调协作——在传统的“多学科”领域之外,进入工程、数学和计算机科学领域——将帮助我们实现这一目标。与此同时,那些处于卫生数据革命前沿的人必须赢得和维持社会的信任,并证明数据共享和重用是改善患者护理的必要步骤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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