Survey: Big Data Application in Biomedical Research

Yvonne Bachiller, P. Busch, M. Kavakli, Len Hamey
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引用次数: 1

Abstract

In recent years, the emergence of diverse applications created a plethora of data and immense sources that can be applied in varying areas of the industry worldwide escalating its capabilities including biomedicine. Subsequently, analytical tools loomed to leverage the availability of massive data to analyze and elicit meaningful information to improve biomedical research and enhance healthcare systems. Algorithms applied in these analytical tools supplements the prognosis of diseases and personalized treatment of fatal diseases. This survey will evaluate algorithms used in bio medical research for personalized precision medicine, dissect the characteristics that made breakthrough in improving the efficiency of the analytical tool and identify the possible applicability in other diseases. It will focus on the machine learning and deep learning algorithms, both supervised and unsupervised that is applied in terminal diseases.
调查:大数据在生物医学研究中的应用
近年来,各种应用程序的出现创造了大量的数据和巨大的资源,可以应用于全球工业的不同领域,包括生物医学在内的能力不断升级。随后,分析工具开始利用海量数据的可用性来分析和提取有意义的信息,以改进生物医学研究和增强医疗保健系统。在这些分析工具中应用的算法补充了疾病的预后和致命疾病的个性化治疗。本调查将评估用于个性化精准医疗的生物医学研究中的算法,剖析在提高分析工具效率方面取得突破的特点,并确定其在其他疾病中的可能适用性。它将专注于机器学习和深度学习算法,包括应用于绝症的监督和无监督算法。
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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