Role of Big Data Analysis for Smart Healthcare in Large Cities
Janjhyam Venkata Naga Ramesh, Nidhi Sindhwani, Asha Yadav, Shambhu Bhardwaj, M. K. Jayanthi Kannan, Rohit Anand, Ankur Gupta · 2024
As the population of large cities grows, healthcare systems face new challenges such as increased patient volume, a lack of resources, and difficulty managing patient data. Big data analysis has emerged as a key tool in healthcare for addressing these difficulties. In this research, we offer a study that employs the Birch clustering algorithm to investigate the importance of big data analysis in smart healthcare in major cities. We use a dataset published by the Centres for Medicare & Medicaid Services that summarizes Medicare beneficiaries’ utilization and payments for surgeries, services, and prescription medications given by individual hospitals, physicians, and other suppliers. Before implementing the Birch clustering technique, we preprocess the data and scale the features. The Elbow technique is used to estimate the best number of clusters, and a scatter plot is used to visualize the generated clusters. We use Principal Component Analysis to minimize the dimensions of the data and generate a scatter plot. The Birch model is fitted to the data, and the dendrogram is shown. Finally, the data points are plotted in a scatter plot with cluster labels. The findings show that Birch clustering is excellent for analyzing healthcare data and can be utilized to construct smart healthcare systems in large cities.