Skip to main content
construction release_alert
Scholars@Duke will be undergoing maintenance April 11-15. Some features may be unavailable during this time.
cancel
Studies in Computational Intelligence

Relational learning for sustainable health

Publication ,  Chapter
Natarajan, S; Peissig, PL; Page, D
January 1, 2016

Sustainable healthcare is a global need and requires better value–better health–for patients at lower cost. Predictive models have the opportunity to greatly increase value without increasing cost. Concrete examples include reducing heart attacks and reducing adverse drug events by accurately predicting them before they occur. In this paper we examine howaccurately such events can be predicted presently and discuss a machine learning approach that produces accurate such predictive models.

Duke Scholars

DOI

Publication Date

January 1, 2016

Volume

645

Start / End Page

245 / 264

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4611 Machine learning
  • 4602 Artificial intelligence
  • 4007 Control engineering, mechatronics and robotics
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Natarajan, S., Peissig, P. L., & Page, D. (2016). Relational learning for sustainable health. In Studies in Computational Intelligence (Vol. 645, pp. 245–264). https://doi.org/10.1007/978-3-319-31858-5_11
Natarajan, S., P. L. Peissig, and D. Page. “Relational learning for sustainable health.” In Studies in Computational Intelligence, 645:245–64, 2016. https://doi.org/10.1007/978-3-319-31858-5_11.
Natarajan S, Peissig PL, Page D. Relational learning for sustainable health. In: Studies in Computational Intelligence. 2016. p. 245–64.
Natarajan, S., et al. “Relational learning for sustainable health.” Studies in Computational Intelligence, vol. 645, 2016, pp. 245–64. Scopus, doi:10.1007/978-3-319-31858-5_11.
Natarajan S, Peissig PL, Page D. Relational learning for sustainable health. Studies in Computational Intelligence. 2016. p. 245–264.

DOI

Publication Date

January 1, 2016

Volume

645

Start / End Page

245 / 264

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4611 Machine learning
  • 4602 Artificial intelligence
  • 4007 Control engineering, mechatronics and robotics