A new application of machine learning in health care

Kaj-Mikael Björk, Emil Eirola, Y. Miché, A. Lendasse
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引用次数: 5

Abstract

In our ever more complex world, the field of analytics has dramatically increased its importance. Gut feeling is no longer sufficient in decision making, but intuition has to be combined with support from the huge amount of data available today. Even if the amount of data is enormous, the quality of the data is not always good. Problems arise in at least two situations: i) the data is imprecise by nature and ii) the data is incomplete (or there are missing parts in the data set). Both situations are problematic and need to be addressed appropriately. If these problems are solved, applications are to be found in various interesting fields. We aim at achieving significant methodology development as well as creative solutions in the domain of medicine, information systems and risk management. This paper sets focus especially on missing data problems in the field of medicine when presenting a new project in its very first phase.
机器学习在医疗保健领域的新应用
在我们日益复杂的世界中,分析领域的重要性急剧增加。在做决定时,直觉不再是足够的,直觉必须与今天大量可用数据的支持相结合。即使数据量是巨大的,数据的质量也并不总是好的。至少在两种情况下会出现问题:i)数据本质上是不精确的,ii)数据是不完整的(或数据集中有缺失的部分)。这两种情况都有问题,需要妥善处理。如果解决了这些问题,就可以在各种有趣的领域中找到应用。我们的目标是在医学,信息系统和风险管理领域实现重要的方法开发以及创造性的解决方案。本文在提出一个新项目的第一阶段,特别关注医学领域的数据缺失问题。
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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