Advertisement

Smart and Connected Health Projects: Characteristics and Research Challenges

  • Jiangping ChenEmail author
  • Minghong Chen
  • Jingye Qu
  • Haihua Chen
  • Juncheng Ding
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10983)

Abstract

The Smart and Connected Health (SCH) program at the National Science Foundation (NSF) has been established as a stand-alone solicitation since 2012. This article reviews and analyzes the 100 projects that have been funded since 2012 to understand their characteristics and the research challenges they have addressed in SCH. Descriptive analysis, topic analysis based on Latent Dirichlet Allocation (LDA), and comparative content analysis were performed. Our study indicated that NSF SCH projects, featured with collaborative and multidisciplinary research endeavor, have been exploring more than 36 diseases or health problems, and five major research challenges including electronic health record (HER) data processing, system design or computational model building, personalized or patient-centered medicine, training and education, and privacy preserving. Much more research projects are needed to investigate algorithms, devices, and impacts of smart health on diseases and communities.

Keywords

Smart and connected health NSF projects Text analysis Data analysis 

References

  1. 1.
    Pramanik, Md.I., Lau, R.Y.K., Demirkan, H., Azad, Md.A.K.: Smart health: big data enabled health paradigm within smart cities. Expert. Syst. Appl. 87, 370–383 (2017)CrossRefGoogle Scholar
  2. 2.
    National Science Foundation: Smart and Connected Health (SCH): Connecting Data, People and Systems (2018). https://www.nsf.gov/pubs/2018/nsf18541/nsf18541.htm
  3. 3.
    Clancy, C.M.: Getting to “smart” health care. Health Aff. 25(6), 589–592 (2006)CrossRefGoogle Scholar
  4. 4.
    National Science Foundation: Awards advanced search (2018). https://www.nsf.gov/awardsearch/advancedSearch.jsp
  5. 5.
    Bird, S., Klein, E., Loper, E.: Natural language processing with Python – analyzing text with the natural language toolkit (2018). http://www.nltk.org/book/
  6. 6.
    WordArt.com. https://wordart.com/. Accessed 2018
  7. 7.
    Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3(Jan), 993–1022 (2003)zbMATHGoogle Scholar
  8. 8.
    Rosen-Zvi, M., Griffiths, T., Steyvers, M., Smyth, P.: The author-topic model for authors and documents. In: Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence, pp. 487–494. AUAI Press (2004)Google Scholar
  9. 9.
    Steyvers, M., Smyth, P., Rosen-Zvi, M., Griffiths, T.: Probabilistic author-topic models for information discovery. In: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 306–315. ACM (2004)Google Scholar
  10. 10.
    Momeni, A., Rost, K.: Identification and monitoring of possible disruptive technologies by patent-development paths and topic modeling. Technol. Forecast. Soc. Chang. 104, 16–29 (2016)CrossRefGoogle Scholar
  11. 11.
    Kim, M., Park, Y., Yoon, J.: Generating patent development maps for technology monitoring using semantic patent-topic analysis. Comput. Ind. Eng. 98, 289–299 (2016)CrossRefGoogle Scholar
  12. 12.
    Venugopalan, S., Rai, V.: Topic based classification and pattern identification in patents. Technol. Forecast. Soc. Chang. 94, 236–250 (2015)CrossRefGoogle Scholar
  13. 13.
    Nichols, L.G.: A topic model approach to measuring interdisciplinarity at the National Science Foundation. Scientometrics 100, 741–754 (2014)CrossRefGoogle Scholar
  14. 14.
    Gensim. https://radimrehurek.com/gensim/. Accessed 2018
  15. 15.
    Olshansky, S.J., et al.: The future of smart health. Computer 49, 14–21 (2016)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Information ScienceUniversity of North TexasDentonUSA
  2. 2.School of Information ManagementSun Yat-sen UniversityGuangzhouChina
  3. 3.School of Information Technology and MediaBeihua UniversityJilinChina
  4. 4.Department of Computer ScienceUniversity of North TexasDentonUSA

Personalised recommendations