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An Investigation Into the Efficacy of Deep Learning Tools for Big Data Analysis in Health Care

机译:深度学习工具在医疗保健中进行大数据分析的功效调查

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摘要

This article describes how machine learning (ML) algorithms are very useful for analysis of data and finding some meaningful information out of them, which could be used in various other applications. In the last few years, an explosive growth has been seen in the dimension and structure of data. There are several difficulties faced by conventional ML algorithms while dealing with such highly voluminous and unstructured big data. The modern ML tools are designed and used to deal with all sorts of complexities of data. Deep learning (DL) is one of the modern ML tools which are commonly used to find the hidden structure and cohesion among these large data sets by giving proper training in parallel platforms with intelligent optimization techniques to further analyze and interpret the data for future prediction and classification. This article focuses on the use of DL tools and software which are used in past couple of years in various areas and especially in the area of healthcare applications.
机译:本文介绍了机器学习(ML)算法对于数据分析以及从中查找一些有意义的信息非常有用,这些信息可以在其他各种应用程序中使用。在过去的几年中,数据的规模和结构出现了爆炸性的增长。传统的ML算法在处理如此大量和非结构化的大数据时面临着许多困难。现代的ML工具被设计用于处理各种复杂的数据。深度学习(DL)是现代ML工具之一,通常通过在并行平台上使用智能优化技术进行适当的训练以进一步分析和解释数据以供将来预测和使用,从而在这些大数据集中找到隐藏的结构和内聚力。分类。本文重点介绍DL工具和软件的使用,这些工​​具和软件在过去几年中在各个领域,尤其是在医疗保健应用领域中使用。

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