Clinical decisions are more promising and evidence-based, hence, big data analytics to assist clinical decision-making has been expressed for a variety of clinical fields. Due to the sheer size and availability of healthcare data, big data analytics has revolutionized this industry and promises us a world of opportunities. It promises us the power of early detection, prediction, prevention, and helps us to improve the quality of life. Researchers and clinicians are working to inhibit big data from having a positive impact on health in the future. Different tools and techniques are being used to analyze, process, accumulate, assimilate, and manage large amount of healthcare data either in structured or unstructured form. In this review, we address the need of big data analytics in healthcare: why and how can it help to improve life?. We present the emerging landscape of big data and analytical techniques in the five sub-disciplines of healthcare, i.e., medical image analysis and imaging informatics, bioinformatics, clinical informatics, public health informatics and medical signal analytics. We present different architectures, advantages and repositories of each discipline that draws an integrated depiction of how distinct healthcare activities are accomplished in the pipeline to facilitate individual patients from multiple perspectives. Finally, the paper ends with the notable applications and challenges in adoption of big data analytics in healthcare.

临床决策更加有前途且基于证据，因此，已经针对各种临床领域表达了有助于临床决策的大数据分析。由于医疗数据的巨大规模和可用性，大数据分析彻底改变了该行业，并为我们带来了无限的机遇。它向我们保证了早期发现，预测，预防的力量，并帮助我们改善生活质量。研究人员和临床医生正在努力抑制大数据将来对健康产生积极影响。正在使用不同的工具和技术来分析，处理，积累，吸收和管理结构化或非结构化形式的大量医疗数据。在这篇评论中，我们满足了医疗保健中大数据分析的需求：为什么以及如何帮助改善生活？我们介绍了医疗保健五个子学科中的大数据和分析技术的新兴前景，即医学图像分析和成像信息学，生物信息学，临床信息学，公共卫生信息学和医学信号分析。我们介绍了每个学科的不同架构，优势和存储库，它们对如何在管道中完成不同的医疗保健活动以从多个角度促进单个患者进行了综合描述。最后，本文以在医疗保健中采用大数据分析的显着应用和挑战结尾。公共卫生信息学和医疗信号分析。我们介绍了每个学科的不同架构，优势和存储库，它们对如何在管道中完成不同的医疗保健活动以从多个角度促进单个患者进行了综合描述。最后，本文以在医疗保健中采用大数据分析的显着应用和挑战结尾。公共卫生信息学和医疗信号分析。我们介绍了每个学科的不同架构，优势和存储库，它们对如何在管道中完成不同的医疗保健活动以从多个角度促进单个患者进行了综合描述。最后，本文以在医疗保健中采用大数据分析的显着应用和挑战结尾。