Availability of large and complex healthcare data is an important resource for gaining any valuable insight. An in-depth analysis is required to utilize this resource effectively. Due to this, researchers and professionals have embarked on designing various computational techniques. Network Analysis is one such technique for analysing heterogeneous data through visualizations. The fusion of Network Analysis with other prominent techniques and technologies forms a foundation for developing robust framework so as to perform predictive analysis in different applications. Such analyses often act as a baseline for medical predictions because of the interdependent and complex nature of data involved. It has been used in medical predictive tasks like discovering unknown disease associations for drug repositioning or comprehending disease progression. This review has been designed to firstly introduce Network Analysis as an emerging computational and analytical solution for any complex data so as to develop a base for the readers. Then, it reviews its current state in healthcare domain so as to realize its future prospects. The network analytic models developed with the discussed techniques and challenges would be valuable for the future of predictive, preventive and progressive healthcare solutions leading to the notion of personalized medicine.

大型和复杂的医疗保健数据的可用性是获取任何有价值的见解的重要资源。需要进行深入分析才能有效利用此资源。因此，研究人员和专业人员开始着手设计各种计算技术。网络分析是一种通过可视化分析异构数据的技术。网络分析与其他著名技术的融合为开发健壮的框架以在不同应用程序中执行预测分析奠定了基础。由于所涉及数据的相互依赖性和复杂性，此类分析通常充当医学预测的基准。它已用于医学预测性任务，例如发现未知的疾病关联以重新定位药物或理解疾病的进展。这篇综述的目的是首先介绍网络分析，将其作为针对任何复杂数据的新兴计算和分析解决方案，从而为读者奠定基础。然后，它回顾其在医疗领域的现状，以实现其未来前景。利用所讨论的技术和挑战开发的网络分析模型对于导致个性化医学概念的预测性，预防性和渐进性医疗保健解决方案的未来将是有价值的。