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Machine learning for personalized medicine: Predicting primary myocardial infarction from electronic health records

Publication ,  Journal Article
Weiss, JC; Natarajan, S; Peissig, PL; McCarty, CA; Page, D
Published in: AI Magazine
January 1, 2012

Electronic health records (EHRs) are an emerging relational domain with large potential to improve clinical outcomes. We apply two statistical relational learning (SRL) algorithms to the task of predicting primary myocardial infarction. We show that one SRL algorithm, relational functional gradient boosting, outperforms propositional learners particularly in the medically relevant high-recall region. We observe that both SRL algorithms predict outcomes better than their propositional analogs and suggest how our methods can augment current epidemiological practices. Copyright © 2012, Association for the Advancement of Artificial Intelligence.

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Published In

AI Magazine

DOI

ISSN

0738-4602

Publication Date

January 1, 2012

Volume

33

Issue

4

Start / End Page

33 / 45

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4611 Machine learning
  • 4602 Artificial intelligence
  • 1702 Cognitive Sciences
  • 0801 Artificial Intelligence and Image Processing
 

Citation

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Weiss, J. C., Natarajan, S., Peissig, P. L., McCarty, C. A., & Page, D. (2012). Machine learning for personalized medicine: Predicting primary myocardial infarction from electronic health records. AI Magazine, 33(4), 33–45. https://doi.org/10.1609/aimag.v33i4.2438
Weiss, J. C., S. Natarajan, P. L. Peissig, C. A. McCarty, and D. Page. “Machine learning for personalized medicine: Predicting primary myocardial infarction from electronic health records.” AI Magazine 33, no. 4 (January 1, 2012): 33–45. https://doi.org/10.1609/aimag.v33i4.2438.
Weiss JC, Natarajan S, Peissig PL, McCarty CA, Page D. Machine learning for personalized medicine: Predicting primary myocardial infarction from electronic health records. AI Magazine. 2012 Jan 1;33(4):33–45.
Weiss, J. C., et al. “Machine learning for personalized medicine: Predicting primary myocardial infarction from electronic health records.” AI Magazine, vol. 33, no. 4, Jan. 2012, pp. 33–45. Scopus, doi:10.1609/aimag.v33i4.2438.
Weiss JC, Natarajan S, Peissig PL, McCarty CA, Page D. Machine learning for personalized medicine: Predicting primary myocardial infarction from electronic health records. AI Magazine. 2012 Jan 1;33(4):33–45.

Published In

AI Magazine

DOI

ISSN

0738-4602

Publication Date

January 1, 2012

Volume

33

Issue

4

Start / End Page

33 / 45

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4611 Machine learning
  • 4602 Artificial intelligence
  • 1702 Cognitive Sciences
  • 0801 Artificial Intelligence and Image Processing