Network Analysis as a Computational Technique and Its Benefaction for Predictive Analysis of Healthcare Data: A Systematic Review

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.