Smart and Connected Health: What Can We Learn from Funded Projects?

Abstract

Following an integrated data analytics framework that includes descriptive analysis and multiple automatic content analysis, we examined 265 projects that have been funded by the National Science Foundation (NSF) under the Smart and Connected Health (SCH) program. Our analysis discovered certain characteristics of these projects, including the distribution of the funds over years, the leading organizations in SCH, and the multidisciplinary nature of these projects. We also conducted content analysis on project titles and automatic analysis on the abstracts of the projects, including term frequency/word cloud analysis, clustering analysis, and topic modeling using Biterm method. Our analysis found that five main research areas were explored in these projects: system or platform development, modeling or algorithmic development for various purposes, designing smart health devices, clinical data collection and application, and education and academic activities of SCH. Together we obtained a comparatively fair understanding of these projects and demonstrated how different analytic approaches could complement each other. Future research will focus on the impact of these projects through an analysis of their publications and citations.