Stabilizing sparse Cox model using statistic and semantic structures in electronic medical records

Shivapratap Gopakumar, Tu Dinh Nguyen, Truyen Tran, Dinh Phung, Svetha Venkatesh

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Stability in clinical prediction models is crucial for transferability between studies, yet has received little attention. The problem is paramount in high dimensional data, which invites sparse models with feature selection capability. We introduce an effective method to stabilize sparse Cox model of time-to-events using statistical and semantic structures inherent in Electronic Medical Records (EMR). Model estimation is stabilized using three feature graphs built from (i) Jaccard similarity among features (ii) aggregation of Jaccard similarity graph and a recently introduced semantic EMR graph (iii) Jaccard similarity among features transferred from a related cohort. Our experiments are conducted on two real world hospital datasets: a heart failure cohort and a diabetes cohort. On two stability measures - the Consistency index and signal-to-noise ratio (SNR) - the use of our proposed methods significantly increased feature stability when compared with the baselines.

Original languageEnglish
Title of host publicationAdvances in Knowledge Discovery and Data Mining
Subtitle of host publication19th Pacific-Asia Conference, PAKDD 2015 Ho Chi Minh City, Vietnam, May 19–22, 2015 Proceedings, Part II
EditorsTru Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Cheung, Hiroshi Motoda
Place of PublicationCham Switzerland
PublisherSpringer
Pages331-343
Number of pages13
ISBN (Electronic)9783319180328
ISBN (Print)9783319180311
DOIs
Publication statusPublished - 2015
Externally publishedYes
EventPacific-Asia Conference on Knowledge Discovery and Data Mining 2015 - Ho Chi Minh City, Vietnam
Duration: 19 May 201522 May 2015
Conference number: 19th
https://web.archive.org/web/20150429212339/http://www.pakdd2015.jvn.edu.vn/
https://link.springer.com/book/10.1007/978-3-319-18038-0

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume9078
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferencePacific-Asia Conference on Knowledge Discovery and Data Mining 2015
Abbreviated titlePAKDD 2015
CountryVietnam
CityHo Chi Minh City
Period19/05/1522/05/15
Internet address

Cite this

Gopakumar, S., Nguyen, T. D., Tran, T., Phung, D., & Venkatesh, S. (2015). Stabilizing sparse Cox model using statistic and semantic structures in electronic medical records. In T. Cao, E-P. Lim, Z-H. Zhou, T-B. Ho, D. Cheung, & H. Motoda (Eds.), Advances in Knowledge Discovery and Data Mining: 19th Pacific-Asia Conference, PAKDD 2015 Ho Chi Minh City, Vietnam, May 19–22, 2015 Proceedings, Part II (pp. 331-343). (Lecture Notes in Computer Science ; Vol. 9078). Springer. https://doi.org/10.1007/978-3-319-18032-8_26